#and the studies i can find have relatively low data pools

[grinchwrapsupreme]

sitting here scanning through research papers about thymomas trying to figure out if Wilson could have had cancer the entire series because i’ve got problems

the answer is yes by the way

[local-hellhound-steals-spaghetti]

Hm nope novel behaviours, play behaviours and locomotive play/innovative travelling behaviour are not an argument for cetaceans inherently needing more space in human care.

Yes, cetaceans aren't as simplistic as food-travel-food, but in the wild they have a limited energy budget on what they can spend time on doing.

It's why irresponsible people harassing them on boats and jet skis, and even as a chartered dolphin swimming/watching experience, can be so harmful. Because they have to eat a certain number of calories in order to be able to survive and be able to fuel things like play.

Bow/wake riding, for instance, is an energy saving behaviour. By swimming in the boat's wake, dolphins can cruise without expending energy. Whereas, big stampedes and porpoising is going to happen as a last ditch effort to get to or away from something at speed -that's a huge energy expenditure.

Not to mention diving, which is a massive energy cost and requires specific biological adaptations - which we wouldn't see in the coastal bottlenose dolphin ecotype (the most common ecotype housed in zoos and aquariums) because they have successfully adapted to living in coastal inlets, lagoons and usually no more than 10m of water depth

Aerial behaviour like breaching is not always play but can also be a warning or a threat display. Rubbing beach visits are another energetic cost but it is a reinforcing behaviour and I would hypothesize that visits to the beach depend on how much food intake the orcas are able to have. These behaviours all have a function and there's always a cost to them as a wild animal living in what is essentially a food desert.

Distance travelled and any migration choice is going to depend on things like seasonal water temperature changes, resource availability, type of prey and prey specialisations, threats and stressors - such as boat noise, human activity, underwater noise, predators ect.

A good example of a population that has a small home range and very limited migration is the most studied coastal bottlenose dolphin population in the world - the Sarasota dolphins. In a study spanning five decades of four generations of dolphins, the authors characterise this population by a high level of multigenerational site fidelity and low levels of emigration and immigration. This also why we have so much data on them - they're a lot easier to study if they don't travel miles and miles every day.

In a UK and Irish population of coastal bottlenose dolphins, longer distance travelled was thought to be more related to anthropogenic (human) threats.

In human care, we now have extensive data from multiple facilities across the world that discusses movement of bottlenose dolphins and what affects it:

The results showed that enrichment programs were strongly related to both ODBA (Overall dynamic body acceleration) and ADT (Average Distance Travelled per hour). Scheduling predictable training session times was also positively associated with ADT. The findings suggested that habitat characteristics had a relatively weak association with ODBA and were not related to ADT. In combination, the results suggested that management practices were more strongly related to activity levels than habitat characteristics.

This means that habitat characteristics like size and depth had less influence on dolphin movement than things like enrichment and management. What this tells us is that "make tank bigger" or "make it more natural" are not the things that the dolphins actually care about.

When I worked with dolphins, even in large sea pens of up to 10m in depth (depending on the tides), the dolphins spent more time at the surface, people watching and socialising with each other. They didn't just swim and dive for the sake of it. It needs to have a function.

They also did lot of aerial based play without trainers around, which was always fun to watch.

In another facility, our med pool was the smallest pool but was also in the middle of the docks so trainers would stand around and talk and plan there. When we gave them free access to that pool, we had about five dolphins all cramming themselves in there like sardines so they could be closer to the people. Why? Because of the reinforcement history with people. Because they had positive associations with people and relationships with the trainers and wanted to be close. This is also why when people feed wild dolphins it gets so dangerous for them.

They're smart and they learn quickly about what works.

All behaviour has a function. That is the most important thing to remember, even if you never studied animal behaviour and ethology before.

We have no data to suggest that dolphins and whales in human care inherently require x amount of space in order to have good welfare. If sanctuaries truly want to be the future, then they need to give us that data. Rather than lobby governments and lie to the general public about cetacean welfare.

It's also interesting to me how the same people who say these animals are soooo intelligent also can't recognise how intelligence is often correlated with adaptability.

Bottlenose dolphins in particular have adapted to a huge range of different environments, likewise with killer whales. Yet there seems to be a prevailing belief that their intelligence makes them a bad fit for living in human care. Rather than the reason for their success and ability to adapt and develop specific behavioural repertoires and cultures of their own.

bottlenose dolphins travel 100 kilometers a day, there is absolutely no way to properly house them

They travel that distance to search for food, not because they just love going nonstop. Nomadic animals tend to stop traveling if they find a reliable source of food and their other needs are met.

[mostlysignssomeportents]

Machine learning's crumbling foundations

Technological debt is insidious, a kind of socio-infrastructural subprime crisis that’s unfolding around us in slow motion. Our digital infrastructure is built atop layers and layers and layers of code that’s insecure due to a combination of bad practices and bad frameworks.

Even people who write secure code import insecure libraries, or plug it into insecure authorization systems or databases. Like asbestos in the walls, this cruft has been fragmenting, drifting into our air a crumb at a time.

We ignored these, treating them as containable, little breaches and now the walls are rupturing and choking clouds of toxic waste are everywhere.

https://pluralistic.net/2021/07/27/gas-on-the-fire/#a-safe-place-for-dangerous-ideas

The infosec apocalypse was decades in the making. The machine learning apocalypse, on the other hand…

ML has serious, institutional problems, the kind of thing you’d expect in a nascent discipline, which you’d hope would be worked out before it went into wide deployment.

ML is rife with all forms of statistical malpractice — AND it’s being used for high-speed, high-stakes automated classification and decision-making, as if it was a proven science whose professional ethos had the sober gravitas you’d expect from, say, civil engineering.

Civil engineers spend a lot of time making sure the buildings and bridges they design don’t kill the people who use them. Machine learning?

Hundreds of ML teams built models to automate covid detection, and every single one was useless or worse.

https://pluralistic.net/2021/08/02/autoquack/#gigo

The ML models failed due to failure to observe basic statistical rigor. One common failure mode?

Treating data that was known to be of poor quality as if it was reliable because good data was not available.

Obtaining good data and/or cleaning up bad data is tedious, repetitive grunt-work. It’s unglamorous, time-consuming, and low-waged. Cleaning data is the equivalent of sterilizing surgical implements — vital, high-skilled, and invisible unless someone fails to do it.

It’s work performed by anonymous, low-waged adjuncts to the surgeon, who is the star of the show and who gets credit for the success of the operation.

The title of a Google Research team (Nithya Sambasivan et al) paper published in ACM CHI beautifully summarizes how this is playing out in ML: “Everyone wants to do the model work, not the data work: Data Cascades in High-Stakes AI,”

https://storage.googleapis.com/pub-tools-public-publication-data/pdf/0d556e45afc54afeb2eb6b51a9bc1827b9961ff4.pdf

The paper analyzes ML failures from a cross-section of high-stakes projects (health diagnostics, anti-poaching, etc) in East Africa, West Africa and India. They trace the failures of these projects to data-quality, and drill into the factors that caused the data problems.

The failures stem from a variety of causes. First, data-gathering and cleaning are low-waged, invisible, and thankless work. Front-line workers who produce the data — like medical professionals who have to do extra data-entry — are not compensated for extra work.

Often, no one even bothers to explain what the work is for. Some of the data-cleaning workers are atomized pieceworkers, such as those who work for Amazon’s Mechanical Turk, who lack both the context in which the data was gathered and the context for how it will be used.

This data is passed to model-builders, who lack related domain expertise. The hastily labeled X-ray of a broken bone, annotated by an unregarded and overworked radiologist, is passed onto a data-scientist who knows nothing about broken bones and can’t assess the labels.

This is an age-old problem in automation, pre-dating computer science and even computers. The “scientific management” craze that started in the 1880s saw technicians observing skilled workers with stopwatches and clipboards, then restructuring the workers’ jobs by fiat.

Rather than engaging in the anthropological work that Clifford Geertz called “thick description,” the management “scientists” discarded workers’ qualitative experience, then treated their own assessments as quantitative and thus empirical.

http://hypergeertz.jku.at/GeertzTexts/Thick_Description.htm

How long a task takes is empirical, but what you call a “task” is subjective. Computer scientists take quantitative measurements, but decide what to measure on the basis of subjective judgment. This empiricism-washing sleight of hand is endemic to ML’s claims of neutrality.

In the early 2000s, there was a movement to produce tools and training that would let domain experts produce their own tools — rather than delivering “requirements” to a programmer, a bookstore clerk or nurse or librarian could just make their own tools using Visual Basic.

This was the radical humanist version of “learn to code” — a call to seize the means of computation and program, rather than being programmed. Over time, it was watered down, and today it lives on as a weak call for domain experts to be included in production.

The disdain for the qualitative expertise of domain experts who produce data is a well-understood guilty secret within ML circles, embodied in Frederick Jelinek’s ironic talk, “Every time I fire a linguist, the performance of the speech recognizer goes up.”

But a thick understanding of context is vital to improving data-quality. Take the American “voting wars,” where GOP-affiliated vendors are brought in to purge voting rolls of duplicate entries — people who are registered to vote in more than one place.

These tools have a 99% false-positive rate.

Ninety. Nine. Percent.

To understand how they go so terribly wrong, you need a thick understanding of the context in which the data they analyze is produced.

https://5harad.com/papers/1p1v.pdf

The core assumption of these tools is that two people with the same name and date of birth are probably the same person.

But guess what month people named “June” are likely to be born in? Guess what birthday is shared by many people named “Noel” or “Carol”?

Many states represent unknown birthdays as “January 1,” or “January 1, 1901.” If you find someone on a voter roll whose birthday is represented as 1/1, you have no idea what their birthday is, and they almost certainly don’t share a birthday with other 1/1s.

But false positives aren’t evenly distributed. Ethnic groups whose surnames were assigned in recent history for tax-collection purposes (Ashkenazi Jews, Han Chinese, Koreans, etc) have a relatively small pool of surnames and a slightly larger pool of first names.

This is likewise true of the descendants of colonized and enslaved people, whose surnames were assigned to them for administrative purposes and see a high degree of overlap. When you see two voter rolls with a Juan Gomez born on Jan 1, you need to apply thick analysis.

Unless, of course, you don’t care about purging the people who are most likely to face structural impediments to voter registration (such as no local DMV office) and who are also likely to be racialized (for example, migrants whose names were changed at Ellis Island).

ML practitioners don’t merely use poor quality data when good quality data isn’t available — they also use the poor quality data to assess the resulting models. When you train an ML model, you hold back some of the training data for assessment purposes.

So maybe you start with 10,000 eye scans labeled for the presence of eye disease. You train your model with 9,000 scans and then ask the model to assess the remaining 1,000 scans to see whether it can make accurate classifications.

But if the data is no good, the assessment is also no good. As the paper’s authors put it, it’s important to “catch[] data errors using mechanisms specific to data validation, instead of using model performance as a proxy for data quality.”

ML practitioners studied for the paper — practitioners engaged in “high-stakes” model building reported that they had to gather their own data for their models through field partners, “a task which many admitted to being unprepared for.”

High-stakes ML work has inherited a host of sloppy practices from ad-tech, where ML saw its first boom. Ad-tech aims for “70–75% accuracy.”

That may be fine if you’re deciding whether to show someone an ad, but it’s a very different matter if you’re deciding whether someone needs treatment for an eye-disease that, untreated, will result in irreversible total blindness.

Even when models are useful at classifying input produced under present-day lab conditions, those conditions are subject to several kinds of “drift.”

For example, “hardware drift,” where models trained on images from pristine new cameras are asked to assess images produced by cameras from field clinics, where lenses are impossible to keep clean (see also “environmental drift” and “human drift”).

Bad data makes bad models. Bad models instruct people to make ineffective or harmful interventions. Those bad interventions produce more bad data, which is fed into more bad models — it’s a “data-cascade.”

GIGO — Garbage In, Garbage Out — was already a bedrock of statistical practice before the term was coined in 1957. Statistical analysis and inference cannot proceed from bad data.

Producing good data and validating data-sets are the kind of unsexy, undercompensated maintenance work that all infrastructure requires — and, as with other kinds of infrastructure, it is undervalued by journals, academic departments, funders, corporations and governments.

But all technological debts accrue punitive interest. The decision to operate on bad data because good data is in short supply isn’t like looking for your car-keys under the lamp-post — it’s like driving with untrustworthy brakes and a dirty windscreen.

Image: Seydelmann (modified) https://commons.wikimedia.org/wiki/File:GW300_1.jpg

CC BY-SA: https://creativecommons.org/licenses/by-sa/3.0/deed.en

Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY: https://creativecommons.org/licenses/by/3.0/deed.en

[starlightrows]

In The Eye Of The Beholder

Chapter 3

← Previous - Next →

Pairing: Commander Wolffe x reader

Word Count: 2.6k

Warnings: Oral (m and f receiving), mild anti-clone sentiments,

Summary: Commander Wolffe returns to Coruscant for a check in appointment for the study, and scores another date with you!

As time passes the irritated skin around the scar crossing Wolffe’s face begins to fade. He’s back on deployment now, somewhere in the galaxy leading his troops and carrying out orders. But he is still part of the study on the effectiveness of his prothesetic, he obviously can’t come in for case study updates in person, so instead he has scheduled holo calls with you.

The holocalls should really only take about fifteen minutes, thirty if he’s experiencing issues that require scheduling an in person appointment for adjustment or troubleshooting. But each call lands up being closer to an hour, or two depending on how much time he could truly get away with not being on duty.

You talk about your job, he talks about the war effort. You tell him funny stories from your time studying in medical school. He tells you about the stupid things he’s witnessed various memebrs of his squad (and other battalions) do. You describe what it was like growing up on your homeworld. He describes growing up with three million siblings on a planet that never had a day without rain. Food, music, sleeping habits, things you love, things you hate. The two of you never struggle to find something to talk about.

When he isn’t talking to you on holocalls, you’re always on his mind. Every little thing he sees and does, he finds himself thinking of what kind of comment you would make on the situation. Would you laugh at his brother's antics, or scold them alongside him? What advice would you provide when he is faced with a tough decision? He finds himself looking up into the night sky when stationed on far away planets and wondering just how much distance is between the two of you at this moment, and how long would it be before he could close that distance?

His answer comes sooner than he expected it would. General Plo informs him that the battalion will be returning to Coruscant for the purpose of several squads being transferred or reassigned to the battalion as well as the General needed to attend a series of council meetings in person. General Plo also mentioned that it would be best if he contacted you to schedule a check in for his prosthetic.

Briefly Wolffe wondered if the General knew of his evening he spent off the base with you, but ultimately decided two things. He probably did not, the General is a busy man with many responsibilities, too many to notice the comings and goings of every trooper (or commander) that serves under him. And, even if he did, he didn’t care.

Wolffe uses the excuse to schedule a case study appointment to take over an hour to himself in his quarters talking to you on the coms. He tells you he is returning to Coruscant, and he’ll be stationed there for at least four days. Internally he debates asking you outright to go out with him again. He doesn’t normally get much enjoyment from going out to the bars, but he had so much fun dancing with you last time. To his delight you beat him to the punch.

“So, if you’re gonna be planetside for a little while would you consider coming with me to see some live music and have a couple drinks?” You ask with a hint of heat creeping up into your cheeks. You’ve been looking forward to taking a night off to enjoy this free outdoor concert, but if Wolffe could come with you it would be all the more special.

The grouchy commander with a charming smile and quick wit has grown on you. After he tried to leave before, you were afraid that you’d made a mistake inviting him back to your apartment for sex. But he’s proven you wrong in the last couple months. He’s eager and engaged in your biweekly holocalls. And moreso, he seems eager to see you again.

“I could go for some music and drinks. You gonna dance with me again?” he teases

“Get enough drinks in me and you just might get your wish, commander”

In a few days time, you hear from him that he’s arrived on Coruscant and he’s looking forward to seeing you. Unfortunately you can’t get away from work the first day he’s planetside, with your date scheduled for the second day of his shore leave. You’re distracted throughout that day, thinking about seeing him again. You briefly considered comming him at the end of your shift to invite him back to your apartment. But you decide against it, he’s probably enjoying some downtime with his brothers or by himself, and he’s already agreed to spend time with you tomorrow.

Your assumption is partially correct. He is spending some downtime with his brothers in the barracks in the Coruscant base, they’re passing around a bottle of spotchka playing drinking games. Wolffe is having a good time, but he would honestly rather be with you.

The next morning he turns up at your office in his officers uniform for his case study appointment. You welcome him inside in a professional manner, but the second the door is closed you take his hand and lean up to kiss his cheek.

“Welcome back Commander,”

The appointment is relatively quick, just a series of eye movement tests and a questionnaire on symptoms and side effects he’s experienced since having the prosthetic placed. Though it does take all of your concentration to focus on actually collecting the data and not getting sidetracked by flirty conversation. There will be time enough for that later.

When the appointment is finished, you excuse yourself to go to the fresher and change into something more appropriate for spending the day out. You returned looking lovely in a comfortable but stylish outfit. You lock up your office and the two of you set out for the day. The concert isn’t until later in the afternoon, leaving plenty of time to stroll through the various levels of the city.

As you go along, you begin to notice more and more eyes on the pair of you. Many civilians are of the opinion that the clones should not be permitted to spend their off hours among the population of civilized planets. People are afraid of them, bred for war… the words scary, hostile, and unstable often get thrown around. You make a point to keep in step with Wolffe and enjoy every moment of your time with him. People can stare all they want, you’ve been looking forward to this.

The pair of you arrive at the outdoor venue and find a high table that gives you a good view of that stage without being too close. You order drinks and finger food to snack on while you wait for the concert to start. The sun is quickly setting, the lights meant to illuminate the stage and patio come on.

Wolffe looks dashing in his officers uniform, but you can’t decide if it is more or less comfortable than the armor. You’ll have to ask him later, because now the musicians are starting to play. The music is fun and lively, loud enough to drown out the two of you talking and laughing, but not loud enough you can’t hear each other like at the club last time.

Wolffe didn’t initially think going to see live music in a small venue like this would be enjoyable, he’s not really a music person as it is. But he has a great time, music is so much better hearing it in person, and all the more fun when you have a pretty date who likes to dance after a couple drinks.

It’s not raunchy sexually motivated dancing like before, though that was fun too, your dancing tonight is playful and fun. Your smile shines bright under the twinkling patio lights as he spins and dips you. When the concert ends there is applause from the audience thanking the musicians for their fantastic performance. Wolffe is almost disappointed the show is over, if he had it his way he would get to twirl you around and make you laugh all night long.

Well… that might still be an option in another sense.

Your apartment isn’t too far away, so you walk with your hand in the crook of his arm back to your place. When you get inside you offer him a glass of wine, and sit together in your living room.

“Thanks for coming out with me tonight,” you say warmly

“How could I say no? I love to see you dance,” he replies with a hint of a smirk. You lean in a little and hold his gaze with lips ever so slightly parted, an invitation if he’s willing to accept it.

He does, closing the gap between you to smooth his lips over yours in a kiss. You taste the wine on his lips, dark and sweet. You let your jaw slack a little as his tongue gently pushes past your lips to explore your mouth. Warmth pools low in your tummy, the hand he has placed at your waist is distracting since his thumb slowly stroking over the bottom curve of your breast. But you stay focused, you’ve got something in mind for tonight.

Breaking away from the kiss you make your move, pushing him away from you and back into the couch. “I want to do something for you,” you say in a low sultry tone, hoping he’d trust you enough to lead. He quirks a brow, curious as to your intentions.

You slide off the couch and settle yourself at his feet, pushing his knees open. He eyes you with an air of caution “You don’t have to if you don’t want to,” he says. But damn does he want it, just the sight of you slipping down between his legs already has him half hard.

You run your hands up the outsides of his thighs, and curl your fingers around the top of his trousers. “I want to do this”

He nods and settles back with a smirk “You were planning this weren’t you?” He growls as you work his pants off. You give him an innocent look and bat your eyelashes teasingly. You free his cock from his grays, curving up towards his stomach, hard in anticipation.

You reach out and take him in your hand, licking a stripe up the underside of his shaft and closing your lips over the head. He lets out a groan as you take him deeper into your mouth, sucking as you go.

“Such a good girl taking my cock” he groans.

You begin bobbing your head clinging to his thighs for support. You could feel yourself getting wet with arousal too, his groans and praise getting to you. You use your hand to pump the base of his cock you can’t get to with your mouth, and the other to start massaging his balls. His grunts and moans began getting louder and more desperate.

“I’m close” he moaned “Go on baby, finish me off”

You took him down into your throat, as deep as you could before starting to gag and sucked at him, coaxing him over the edge. You could feel him tightening up, his feral grunts and moans becoming erratic and unrestrained. You pull off of him about half way and open your mouth wide, stroking his cock in quick firm movements. His head drops back onto the couch, grunting and panting as he cums into your waiting mouth.

His head snaps back forward, eyes taking in the sight of you with his cum painted over your lips and in your pretty mouth. He leans forward, reaching out to pinch your cheeks between his thumb and forefinger. You poke your tongue out just a bit, and let him admire the sight of his release.

“Swallow it” he growls

You respond by licking your lower lip and drawing your tongue back into your mouth swallowing whatever you hadn’t already. He surges forward and crashes his lips down on yours. He pulls you up from your spot on the ground, and into his lap. His hands are everywhere, roaming down your back, over the curve of your ass, around to your tummy and up to cup your breasts through your pretty little shirt. He finally breaks the kiss, panting from exertion but still riled up.

“Let me return the favor,” he growls, flipping you over, taking you down to lay back on the couch. He takes his time, peeling off your pants, stripping your top off, and undoing the clasps of your bra. He leans over and kisses you again with a kind of intensity you’ve never experienced before. It’s not exactly rough, it’s hungry and desperate. His hands massage your breasts, deftly rolling your nipples between his fingers. You moan into the kiss.

“You like that baby?” He trails his lips down your neck, and kisses them hollow at the base. You wiggle your hips, the wetness pooling in your nether regions becoming a little uncomfortable. He chuckles darkly, and resumes kissing his way down your body. He stops just at your panty line, looking up at you with a bit of mischief in his eyes.

Without breaking eye contact, he carefully bites the waistband of your panties and begins to drag them down. Your breath hitches at the sight, and you lift your hips up just a bit to help him get them off. When he gets them down to about your knees, he releases them from between his teeth and uses one hand to tear them away.

Then he’s leaning back down, and leaving a trail of wet kisses and little bites from the inside of your knee up your leg, getting closer and closer to where you need him most. His hands slide up the backs of your thighs and lifts you about an inch or two off the couch to his waiting mouth.

His tongue slides between your folds and he begins to lap at your wetness. He teases your aching hole with the most tantalizing strokes of his tongue, switches it up by nosing his way up to your clit and suckling at it, squeezing your ass and moaning into you.

You’re moaning, panting, flushed with heat and getting closer and closer to a release.

“Wolffe,” you moan “please… please… please… make me cum”

He glances up and sees your eyes have fluttered shut, your head tipped back and chest heaving with strained breath. He speeds his movements, suckles at your clit with alternating flicks of his tongue and groans at the sounds of your pleasure.

Your hands twist around the edge of the sofa cushions, needing something to cling onto as your climax overtakes you. Your moans and whimpers stall out, and your voice cuts off as you cum. Your legs tremble in his hold, signaling him to slow down his movements and pull away from your glistening cunt as you come down from your high.

He crawls back over you, catching your lips in another kiss. You taste yourself on him, and come back to reality.

“Stars….” you whisper, breaking the kiss “You didn’t tell me you had a secret talent, Commander”

“If I told you, it wouldn’t be much of a secret would it?” He kisses you again, the desperation has subsided but the hunger is still there.

“You gonna try to take off on me or are you sticking around for breakfast tomorrow?” You tease him. You get the feeling he knew he was welcome to stay again, but still make the joke just in case.

“If the offer is on the table?” He quirks an eyebrow at your comment, and gives you a smirk.

On the table you think to yourself maybe next time….

Tag List: @ems-alexandra @thefact0rygirl @ajeff855

[cordria]

Regret

It was his mother’s birthday.

Danny Fenton slipped through the portal, careful not to be seen. He knew just what to get her - a flower from the depths of the ghost zone. It was a brilliant green rose-like flower with red leaves and thorns rumored to have some sort of magical properties. Danny wasn’t entirely sure what they were, but he knew his mother would love experimenting on it.

Kicking off the little spit of land the portal was located on, he spiraled into the wastes. He’d be home in a couple hours at most. Nobody would even notice he was gone.

--

Vlad Masters settled down at his desk, fingers brushing over the phone. It was Maddie’s birthday today. Slowly, his finger traced up and down the back of the handset, debating what to say. Last time, they hadn’t parted on the best of terms. Vlad was certain she was still harboring a bit of a grudge.

Perhaps he should just send a card.

“Oh grow a pair,” Vlad hissed at himself, picking up the phone. 

The phone rang and rang and rang.

Vlad almost felt relieved when it clicked over to the overly-full voicemail and he got to hang up. Now he could send a card, and not find out what sort of things Maddie had to say about their last meeting.

--

Maddie Fenton was too busy to answer the phone. She was sitting at the kitchen table, staring down at a mess of data, trying to make sense of the numbers. It was just about to come together in her brain - she could feel it - and there was no way she was going to start over just to answer the phone when it was likely a computer telemarketer.

The data showed a bit of information Maddie had taken to calling the resonance-factor. She would send a ping of sound into the ghost zone, much like sonar, and collect data from its reflection. They were using it to create a map of the zone near the portal and track how the ghost zone’s physical layout changed. But she had noticed this strange echoing noise in the sound, and the echoing noise had been slowly getting worse and worse. Now it was messing with the data they were getting back so much their maps were no longer accurate.

But what was causing it? How to stop it from interfering with her exploration? 

--

Danny curled past Skulker’s lair, noticing that it was much quieter than normal. Generally the hunter’s home was a cacophony of noise from his captured prey. Today there were just a few lonely mewls of sound. He hesitated, but shrugged and kept going. Who knew what went through that ghost’s mind.

--

Vlad signed the card with a flourish and set it in the envelope. It was a beautiful card that straddled the difference between felicitations and apologies for his latest choices. He stared down at the hunter green envelope, Maddie’s name already written in silver ink. Oh, how things would be easier if he could just explain the cause of his behavior.

But he couldn’t. That was just the way it was. He would simply have to do better.

He pushed away from his desk, deciding to invisibly drop the card in her home instead of mail it. As he flew out of his house and into the air, Vlad debated where the best place to leave the card was. Despite his initial leanings towards her pillow so she would read it before she went to bed and tenderly hold the card in her sleep, he decided the kitchen table would be more appropriate. 

She was probably going to shred the card anyways, and the paper shredder was in the kitchen. He might as well be realistic - and perhaps she’d be appreciative of the fact that she didn’t have to walk as far.

--

Maddie scribbled on a piece of paper, creating a graph of her odd data. It was an s-shaped curve, growing slowly at first, then quickly, and was now slowing down again. She sat back in her chair.

She’d seen graphs like this in the ghost zone before - it was actually the most common energy growth pattern in that world. Ghosts themselves used a very similar pattern when they were going to be blasting something. A slow gathering of energy, then a quick spike in power, followed by a slow pooling of energy until it hit the appropriate level to create the blast. Of course, in ghosts it happened over tenths of a second instead of over days like this one.

The end of her pen went into her mouth and she chewed at it. 

The graph was hinting at the idea that the ghost zone was in the final build up to something. Perhaps some sort of energy release.

But what? And why?

--

Danny flew deeper into the ghost zone, more and more feeling an odd sense of dread. Of course, a sense of dread in the ghost zone wasn’t exactly unheard-of, but this was definitely a weirder feeling than normal. 

He hesitated at one point, hovering in place and looking around. There were very few ghosts around, and they were mostly the really small ones. 

It was almost like something was… wrong.

He frowned, debating just heading home, when he saw a glowing spot of red and green. “Hey!” he said, grinning and diving down to the floating bit of rock. There was the flower he was looking for! “Perfect.”

Digging a pot and a shovel out of his bag, he settled down next to the flower and started digging it out of the ground. 

Then he’d head home.

--

Vlad’s feet settled on the ground outside of FentonWorks. He paced back and forth for a moment, gathering up the courage to enter into the home. Hopefully his last computer hacks preventing the Fenton’s security system from recognizing him were still in place. Otherwise he’d set off every sensor in the home.

He walked through the back door, making sure he was invisible, and into the kitchen. He hesitated, noticing Maddie sitting at the messy kitchen table, chewing on the end of her pen. That threw a wrench into his plans.

Perhaps he could now leave the card on her pillow… And steal Jack’s at the same time.

He tossed the idea out of his head and walked over, glancing down at what she was doing. Energy graphs. Really basic ghost zone physics that even he understood. So why was she worrying over them?

He squinted closer. An echo in her sonar data.

Resonance.

He let his card fall to the ground, feeling his stomach drop. “Shit,” he whispered.

--

Maddie heard someone breathe a quiet, “shit,” from right behind her ear. She tensed and twirled, weapon going up before she even had identified the fact that there was nothing there. She waited, gun up and aimed towards where the voice had come from.

There was the slightest of cold breezes. A ghost.

“I know you’re there,” she demanded. “How did you get into my house?”

The ghost shifted into view - the vampiric one that was always tormenting Jack. “Why, hello my dear,” it said with a greasy smile.

“Hello nothing,” she snapped. “What are you doing in my house?”

“Why,” the ghost hesitated, “I’m looking at your data. And what an excellent graph you’ve made.” 

Maddie’s eyes narrowed. That wasn’t the whole truth, obviously. The ghost hadn’t known about her data until it had already entered her home. But, based on the quiet exclamation from earlier, the ghost understood the purpose of the graph. And she was… curious. “What does this mean?” she asked, gesturing towards the papers with one hand, the other keeping the gun steady on the ghost’s face.

“It means we need to shut your portal down.”

“Ah… no. I don’t think so.” Maddie tipped her head. “Not without an excellent explanation.”

--

Danny grinned, slipping the shovel back into his backpack and studying his prize. Yeah, he’d done a hack-job on it’s roots - but who would have expected a ghost flower (a dead flower?) to have such an extensive system of roots? Hopefully he hadn’t killed it. He grabbed the pot, tucking it under his arm, and glanced around.

The quiet was unsettling. And there was this… it wasn’t quite a noise. Danny couldn’t quite put his finger on it, but it was something like the rumble of a really low, low tone. That he could feel in his stomach more so than his ears. And it was getting louder.

“I’m going to get out of here too,” Danny muttered, shooting into the air and heading back towards the portal, plant firmly tucked under his arm.

--

Vlad didn’t really have time for an explanation. He needed to shut down the Fenton’s portal, then head home and shut down his own. If he was right, he didn’t need the collateral damage ending up in his town. The city didn’t have the budget for it, and the city’s insurance agent had been quite clear that they weren’t going to cover any Fenton-related damages any longer.

But the weapon Maddie was holding was a powerful one. It would hurt, and perhaps cause permanent damage. He had little choice in the matter.

His fingers curled behind his back, clasping each hand. “Ghosts are immortal, yes? Then there should be an infinite number of them... us, clogging up the ghost zone. So there’s a natural balancing mechanism in the ghost zone. When too many ghosts start to build up in one place, too much energy is taken from the environment and the ghost zone reacts to it by annihilating all the ghosts in the area.”

He watched her blink and take that in.

“When the blast wave goes by, you don’t want to be in the vicinity. Your home doesn’t want to be in the vicinity.”

“I’m not sure that sounds…” 

She was speaking too slowly, obviously trying to think through it, and Vlad simply did not have the time for it. “I can come back and give you the longer explanation and spend hours explaining the data to you, but we do not have a lot of time right now.” 

Her lips tightened. But then she nodded. “I don’t trust ghosts, but I can accept the data points in that sort of direction. You leave, I’ll shut down the portal.”

“I’ll help-”

“You’ll leave.” Maddie’s voice booked no room for disagreement. 

Vlad was quite sure that doing anything other than vanishing would get him shot. He narrowed his eyes, waited a beat more, then vanished and headed home.

--

It took Maddie almost a minute to make sure the ghost was gone. She was spooked by the fact that it could get into her house in the first place - there was a bug in the detection equipment that would need to be sorted out relatively quickly - and had to track down a secondary detector before she was willing to let down her guard.

Shutting down the portal was another story. It was powered by the ghost zone itself, now that it was up and running, and pulling the cord would simply shut down the doors and sensing equipment. There was a way to shut it down, she just didn’t like doing it.

But the ghost had looked spooked. And the data… was pointing in the direction the ghost had indicated. Whatever huge energy blast was building in the ghost zone, she wanted nothing to do with it in her home.

She swore softly and picked up the Fenton Shut-er-Down-her (she hadn’t named it), weighing the grenade-like object in her hand. It would create a huge blast of foam that would block energy from accessing the portal from the other side, shutting it down as effectively as snuffing out a candle by cutting off the oxygen supply.

It would be killer to get the thing reopened. Weeks of work. On the word of a ghost.

Maddie sighed, pulled the activator on the device, and tossed it through the portal, thumbing the doors shut behind it.

--

Danny was twenty feet from the portal when the foam exploded. He pulled up fast, startled by the rapidly expanding white goo. Within seconds, the portal was completely buried.

He settled down on the bit of rock, feeling the environment around him shaking with the force of the whatever-it-was. He walked up to the foam, reaching out to touch it. It was steaming hot and sticky, still bubbling and growing like some sort of alien monster.

Behind the wall of foam, the green glow of the portal vanished. Danny felt the portal shut off deep inside him, like a punch to the gut.

“That doesn’t bode well,” he whispered, setting down the flower (he could come back for it later) and glancing around. “This is unsettling enough for now, let’s just get home. Vlad’s is… that-a-way?”

He took off at top speed.

--

Vlad made it home in nearly record time (not that he had ever timed it, of course, he was far too old to be timing how fast he could fly). He slipped right into the hallway, walking up to the picture that hid his portal. The button clicked under his finger, and the giant painting slid to the side. 

He had a similar problem to Maddie’s - portals are not so easy to shut down when they are powered by the ghost zone itself - however he had a much less elegant and far more expensive solution. He turned the power controls up to maximum. In a matter of moments, the portal would overload, fry the circuits, and cause a controlled blast out into the ghost zone. It would destroy everything in the area (and his portal) but the damage on this side would be minimal, contained by the portal’s door.

“Horrible timing,” he informed the ghost zone as he heard the portal start to whine. He’d known this was coming; the density of the ghosts had been getting too high. The energy in the ghost zone had been feeling more and more fragile. But he’d just been getting settled, got the ghosts to understand to leave him alone, and everything was getting nice and quiet. 

His finger hovered over the controls for the door.

--

Maddie stared at the dark portal. A portion of the foam had come through to this side, effectively gluing the portal shut. Behind the doors, no doubt the device was filled with the steaming foam, covering all the circuits and wires. 

Jack was going to be very unhappy when he got back with her ‘surprise’ birthday cake.

There was a short-ish window of time before the foam set up hard. She would have to start cleaning.

“Danny!” she called. “Come help me get this cleaned up!”

Silence.

--

Danny found the floating purple football and pushed it out of the way. “Found you!” he said, diving forwards.

The portal’s door was closing. Danny picked up speed, but he wasn’t going to make it. In the small space left open, Danny could see Vlad staring back at him.

“Vlad!” he called. “Wait!”

There was an odd expression on Vlad’s face as the door slammed shut, locking the portal shut and locking Danny into the ghost zone: regret.

Danny hovered, not entirely sure what to do. He rubbed his forehead, starting to get a headache from the constant throbbing. Then he turned. He had two options left - Clockwork and Frostbite. He had to get to one of them. They would know what was going on. They’d help.

He had barely started flying when Vlad’s portal ripped itself to shreds. Danny screamed, tucking into a ball and avoiding the worst of the shrapnel. he tumbled out of control, his arm flashing bright pain. By the time he drifted to a stop, goo was oozing down a huge slice in his arm and his ears were ringing and he wasn’t entirely sure which direction was up.

It took a precious few minutes for Danny’s mind to start working again. He flew in the direction he hoped Clockwork’s tower was, worried. Both his parents and Vlad had shut down their portals. The deep sound was getting worse, and the silent emptiness around him was starting to get terrifying.

He flew faster and faster, pushing himself to his limits. He had no idea what was going on, but he wanted out of it.

He hoped this time he wouldn’t be too late.

[gordonwilliamsweb]

What Does Approval of the Pfizer Vaccine for Teens and Preteens Mean for My Child?

Q: The federal government approved the Pfizer vaccine for 12- to 15-year-olds. What does this mean for my child?

This story also ran on PolitiFact. It can be republished for free.

Extending the emergency use of the Pfizer-BioNTech vaccine to preteens and young adolescents adds nearly 17 million more Americans to the pool of those eligible to be immunized against covid-19, helping to build a vaccinated population closer to herd immunity. Moderna and Johnson & Johnson are also testing the efficacy of their vaccines in teens and children.

Although children appear to catch covid less often and develop milder symptoms than adults, they can develop a rare, severe inflammatory response or “long-haul covid” symptoms. It also remains to be seen what, if any, long-term effects these younger patients may experience from covid.

The share of covid cases in children and teens is increasing — nearly a quarter of the new weekly covid cases were found in this age group, as reported May 6 by the American Academy of Pediatrics and the Children’s Hospital Association.

And, though kids have been less likely to develop severe illness, they still can pose a risk to vulnerable people around them because they may not even know they are carrying the virus, as documented by the Centers for Disease Control and Prevention.

Dr. Margaret Stager, a pediatrician and the division director of adolescent medicine at MetroHealth Medical Center in Cleveland, said she has had to explain to her young patients that getting immunized would help their community curb the spread, cut the risk of variants and help society reopen.

“I talk about them doing their part,” Stager said. “That this is all part of them contributing to the greater good.”

The Fine Print

The CDC this week recommended use of the Pfizer vaccine for children ages 12 to 15 after the Food and Drug Administration extended its emergency use authorization to include these preteens and young adolescents. That means this age group now can receive the same shots in the same time frame — 21 days apart — as adults do.

In a reversal of its previous guidance, teens and adults do not need to wait 14 days before or after getting the covid shot to receive a vaccine for another condition. This could be a boon for health care providers who have child patients lagging on other, routine vaccines, which has been a persistent problem during the pandemic.

“It’s a tremendous opportunity to play catch-up,” said Stager.

CDC officials noted in the May 12 Advisory Committee on Immunization Practices’ recommendation that they do not have data specifically looking at potential side effects in patients immunized against covid and other illnesses at the same time. However, the agency made the decision given the strong safety data of the Pfizer-BioNTech shot and previous experience with other immunizations.

This question will become more important as covid vaccines are studied in younger children. Trials are planned to test the vaccine in children as young as 6 months old.

As in adults, the question of how long the immunity lasts in children remains unknown, said Dr. Rebecca Wurtz, an associate professor of infectious diseases at the University of Minnesota. However, she said, it’s likely that any waning immunity detected in adults will also be seen among the young.

“Whatever we learn in adults,” Wurtz said, “kids will be not far behind.”

Whether this approval will prompt schools to require vaccination against covid for K-12 students returning to the classroom this fall is a pending question, said Stager. It is unclear whether federal law allows state authorities to mandate a vaccine that has not yet been fully approved. That said, the government’s approval will also likely play into parents’ decisions about sending their children to summer camp.

What Did the Trial Find?

Pfizer tested the vaccine in 2,260 preteens and young adolescents living in the United States. Researchers followed participants for two months or more, the FDA said. Pfizer’s clinical protocol says the company will continue to follow participants for two years after the second dose.

Results show the vaccine is safe to use in this age group, causing side effects similar to those seen in young adult populations for whom it had already been cleared, according to the FDA in a press release. Those vaccinated also produced a strong immune response — the level of antibodies recorded in this age group was even stronger than what was seen in 16- to 25-year-olds.

The vaccinated group also had no covid cases when tested seven days after their second dose. Sixteen participants out of 978 who did not get the shot but were followed as part of the study as a control group tested positive for the virus. In short, the vaccine was 100% effective in preventing covid, according to the FDA.

Why So Few Kids?

One data point that may give parents pause is the trial’s number of participants. The relatively low number — especially when compared with the tens of thousands enrolled in adult trials — is a reflection of what the researchers were trying to accomplish, said Dr. Kawsar Talaat, an assistant professor of international health at Johns Hopkins University School of Public Health.

Gauging whether the shot was safe for children and if it generated a strong immune response did not require a large study group, she said. Statisticians can calculate how many people a trial needs to generate meaningful results without unnecessarily exposing people to dangerous pathogens like the coronavirus.

In addition, the findings pertaining to the younger age group built on what has already been learned in earlier studies.

“It’s just not practical to do 30,000-person trials over and over with the same vaccine,” Talaat said. Large trials are expensive, she added. Including minors also poses extra challenges, said Stager, such as getting parental consent.

Jerica Pitts, a Pfizer spokesperson, said in an email the company is using a “careful, stepwise approach” to including minors in clinical trials.

Stager said physiological similarities among 12- to 15-year-olds in response to vaccines have previously been documented. Studies related to a vaccine for the human papillomavirus have shown kids at this age generated similar, strong immune responses, too.

Administering the vaccine to preteens and young adolescents in large numbers may reveal additional effects that weren’t detected in the clinical trials, said A. Oveta Fuller, associate professor of microbiology and immunology at the University of Michigan Medical School.

That said, when weighing the threat of the virus versus the vaccine’s proven safety, she said, the choice is clear.

“The thing is the danger is really not so much the vaccines as it is what it protects against,” Fuller said, “and that’s covid disease.”

KHN (Kaiser Health News) is a national newsroom that produces in-depth journalism about health issues. Together with Policy Analysis and Polling, KHN is one of the three major operating programs at KFF (Kaiser Family Foundation). KFF is an endowed nonprofit organization providing information on health issues to the nation.

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[sciencespies]

Why lists of worldwide bird species disagree

https://sciencespies.com/environment/why-lists-of-worldwide-bird-species-disagree/

Why lists of worldwide bird species disagree

How many species of birds are there in the world? It depends on whose count you go by. The number could be as low as 10,000 or as high as 18,000. It’s tough to standardize lists of species because the concept of a “species” itself is a little bit fuzzy.

That matters because conserving biodiversity requires knowing what diversity exists in the first place. So biologists, led by University of Utah doctoral candidate Monte Neate-Clegg of the School of Biological Sciences, set out to compare four main lists of bird species worldwide to find out how the lists differ — and why. They found that although the lists agree on most birds, disagreements in some regions of the world could mean that some species are missed by conservation ecologists.

“Species are more than just a name,” Neate-Clegg says. “They are functional units in complex ecosystems that need to be preserved. We need to recognize true diversity in order to conserve it.”

The results are published in Global Ecology and Biogeography.

On the origin of species

The definition of a species isn’t clear-cut. Some scientists define populations as different species if they’re reproductively isolated from each other and unable to interbreed. Others use physical features to delineate species, while yet others use genetics. Using the genetic definition produces many more species, but regardless of the method, gray areas persist.

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“Species are fuzzy because speciation as a process is fuzzy,” Neate-Clegg says. “It’s a gradual process so it’s very difficult to draw a line and say ‘this is two species’ vs. ‘this is one species.'”

Also, he says, physical features and genetic signatures don’t always diverge on the same timescale. “For example,” he says, “two bird populations may diverge in song and appearance before genetic divergence; conversely, identical populations on different islands may be separated genetically by millions of years.”

Comparing the lists

At this point in the story, it’s time to introduce four lists, each of which purports to include all the bird species in the world. They are:

The Howard and Moore Checklist of the Birds of the World

The eBird/Clements Checklist of Birds of the World

The BirdLife International Checklist of the Birds of the World

The International Ornithological Community (IOC) World Bird List

“Being active field ornithologists who are always trying to ID bird species means that one is always faced with the issue of some species being on one list but not the other,” says Ça?an ?ekercio?lu, associate professor in the School of Biological Sciences. “So our field experience very much primed us to think about this question and inspired us to write this paper.”

The lists have different strengths depending on their application. The BirdLife International list, for example, integrates with the IUCN Red List, which reports on species’ conservation status. The IOC list is updated by experts twice a year, ?ekercio?lu says. The list is open access with comparisons to other major lists, and changes are documented transparently.

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“But as a birdwatcher, I use eBird all the time, which uses the Clements checklist, and that dataset is very powerful in its own right,” Neate-Clegg says. “So there is no single best option.”

One example of the disagreement between lists might be the common bird Colaptes auratus. The eBird list calls it the northern flicker, a woodpecker. But the BirdLife International list delineates the eastern population as the yellow-shafted flicker and the western population as the red-shafted flicker.

In 2020, Neate-Clegg and his colleagues read a study that compared the raptor species on each list, finding that only 68% of species were consistent among all four lists.

“We thought it would be interesting to investigate taxonomic agreement for all 11,000 bird species,” Neate-Clegg says. “More importantly, we wanted to try and work out what species characteristics led to more or less taxonomic confusion.”

They began by collecting the most recent version of each list (the IOC checklist is updated biannually, the researchers write, and the Clements and BirdLife lists annually, while Howard and Moore has not been updated since 2014) and trimming them down to exclude subspecies and any extinct species. Using a few other data processing rules, they assigned a single name to every possible species across all four lists. Then the comparisons began.

Where the lists agree and disagree

The researchers found that the four lists agreed on the vast majority of bird species — 89.5%. For the remaining 10.5%, then, they started to look for patterns that might explain the disagreement. Some of it was likely geographical. Birds from the well-studied Northern Hemisphere were more likely to find agreement than birds from the relatively understudied Southeast Asia and the Southern Ocean.

Some of it was habitat-based. Agreement was higher for large, migratory species in relatively open habitats.

“I think the most surprising result was that agreement was not lower for highly forest-dependent species,” Neate-Clegg says. “We expected these denizens of the rainforest floor to be the most cryptic and hard to study, with more uncertainty on their taxonomic relationships. Yet we found it was actually species of intermediate forest dependency that had lower taxonomic agreement. We believe that these species move about just enough to diverge, but not so much that their gene pools are constantly mixing.”

And part of the issue with species classification on isolated islands, such as those in Southeast Asia and the Southern Ocean, was a phenomenon called “cryptic diversification.” Although islands can foster species diversification because of their isolation, sometimes two populations on different islands can appear very similar, even though their genes suggest that they’ve been isolated from each other for millions of years. So, depending on the definition, two populations could count as two species or as only one.

“In addition,” Neate-Clegg says, “it’s very hard to test the traditional biological species concept on island fauna because we cannot know whether two populations can interbreed to produce fertile young if they are geographically isolated.”

Why it matters

So what if some people disagree on species designations? Conservation actions are usually on the species level, Neate-Clegg says.

“If a population on one island goes extinct, people may care less if it’s ‘just a subspecies,'” he says. “And yet that island is potentially losing a functionally unique population. If it was recognized as a full species it might not have been lost.”

Neate-Clegg hopes the study points ornithologists towards the groups of species that merit additional attention.

“We also want conservation biologists to recognize that cryptic diversity may be overlooked,” he adds, “and that we should consider units of conservation above and below the species level.”

#Environment

[ezatluba]

America Is Running Low on a Crucial Resource for COVID-19 Vaccines

The country is facing a monkey shortage.

SARAH ZHANG

AUGUST 31, 2020

In the past seven months, more than 100 COVID-19 vaccines, therapies, and drugs have been pushed into development. But for any of these treatments to make it to humans, they usually have to face another animal first: a monkey. And here, scientists in the United States say they are facing a bottleneck. There just aren’t enough monkeys to go around.

“Nationally, there is basically a big shortage,” says Koen Van Rompay, an infectious-disease scientist at the California National Primate Research Center. Primate research in the U.S. is expensive and often controversial, making it challenging even in normal circumstances. The pandemic has made acquiring monkeys even harder. “We can’t find any rhesus any longer. They’ve completely disappeared,” says Mark Lewis, the CEO of Bioqual, a contract research organization that specializes in animal testing. Scientists in academia and industry alike are all competing for a limited pool of monkeys.

The reasons for the shortage are threefold. First, COVID-19 has created extraordinary demand for monkeys. Second, this coincided with a massive drop in supply from China, which provided 60 percent of the nearly 35,000 monkeys imported to the U.S. last year and which shut off exports after COVID-19 hit. And third, these pandemic-related events are exacerbating preexisting monkey shortfalls. A 2018 National Institutes of Health report had found that NIH-funded national primate centers would be unable to meet future demand and specifically discussed a “strategic monkey reserve” to provide “surge capability for unpredictable disease outbreaks.” A disease outbreak is upon us; the strategic monkey reserve was never created.

Furthermore, monkeys infected with COVID-19 have to be kept in Animal Biosafety Level 3 labs, which have specific design and ventilation requirements to prevent the spread of pathogens. The U.S. has a limited number of ABSL-3 labs.

The result, Van Rompay says, is that he gets emails and calls weekly from companies looking to test COVID-19 treatments at the California research center, one of the seven NIH-funded primate centers that work with both academic and industry researchers. “I have to tell them, ‘I’m sorry, we are not allowed to start your research,’” he says. With so much demand for monkeys, the NIH is now centrally deciding which studies can use the national primate centers under a public-private initiative called Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV), creating a new bureaucratic bottleneck. Meanwhile, non-COVID-19 research is also getting pushed aside.

Monkeys account for just 0.5 percent of the animals used in U.S. biomedical research, but they typically represent the last step before human clinical trials. They are closely related to humans, after all—so closely related that scientists refer to the research animals as, technically, “nonhuman primates.” For example, monkey and human immune systems are so similar that vaccine studies can use the same tests to measure antibodies in both. “Literally the same test,” says Skip Bohm, the associate director of the Tulane National Primate Research Center. The similarity means that monkeys are also a good model for testing the agents that help boost the effectiveness of a vaccine, says JoAnne Flynn, a vaccine researcher at the University of Pittsburgh.

As COVID-19 vaccine development has moved forward at an unprecedented pace, though, some pharmaceutical companies have started human trials before monkey studies have concluded. And with monkeys so hard to come by, others are wondering if certain studies can be skipped altogether. Linda Marbán, the CEO of the biotech company Capricor Therapeutics, says her company originally tried to test its vaccine candidates at the California primate center. It couldn’t get in. She’s now exploring how to go straight into human-safety trials.

Scientists who work with primates, however, say that the animal research still offers certain advantages. Monkeys can be challenged—that is, deliberately infected with COVID-19 after being given an experimental vaccine. Researchers can then follow the animals’ exact progression of disease or lack thereof, tracking how quickly antibody levels shoot up or whether a vaccine reduces how long the monkey sheds the virus. These details are harder to get in human trials because people are naturally exposed to COVID-19 and aren’t being monitored every day. (Although some researchers have proposed human challenge trials for COVID-19, the idea is controversial and none has begun.)

Primate research can also be used to study safety in vulnerable populations, says Sallie Permar, a vaccine scientist at Duke University who is planning a study with Van Rompay to look at how infant monkeys respond to several of the leading COVID-19 vaccine candidates. While young children rarely get seriously ill from COVID-19, they can spread it, so vaccinating kids is likely important for reopening schools. But current vaccine trials are mostly restricted to healthy participants ages 18 and up. Without testing the shots in children, it will remain unclear whether COVID-19 vaccines are actually safe and effective for them. “Those trials are difficult to plan and are often not pursued by vaccine companies,” Permar says. She hopes that showing the vaccines are safe and effective in infant monkeys will encourage pharmaceutical companies to test vaccines in children.

Primates are not always the best animal model for every aspect of the disease. Most monkeys, including rhesus macaques and cynomolgus macaques, which are the two most widely used species, get only mildly sick from COVID-19. To study severe illness, scientists are turning to animals such as hamsters. COVID-19-infected hamsters develop lethargy, rapid breathing, and weight loss of up to 11 percent. Plus, says Vineet Menachery, a virologist at the University of Texas Medical Branch, “in terms of a model, hamsters breed well. They’re small enough; they’re easy enough to handle.”

Nonhuman primates are the opposite in this regard. They do not breed well, they’re relatively big animals, and they’re expensive to care for. That’s why nonhuman-primate studies are the last step, not the first, in the development process before human trials. Van Rompay says that he advises companies trying to do research at the primate center to gather data in rodents as an interim step. “Doing experiments in rodents is a lot cheaper,” he says. “The most promising ones can then be tested in nonhuman primates.”

Breeding more monkeys in the U.S. will take years, along with sustained funding. The country has a limited number of breeding facilities, including the NIH-funded primate centers. Monkeys set aside for breeding can’t be used for research either.

Decades ago, the vision for a network of federally funded primate-research centers grew out of an NIH scientist’s visit to a Soviet monkey lab in 1956. But the centers have struggled to get more funding in recent years, and one that was affiliated with Harvard closed for financial reasons in 2015. (It had also been subject to protests and an investigation following several monkey deaths.) Several years ago, Van Rompay says, the California center began breeding more monkeys to meet research demand, but the funding for maintaining the colonies didn’t go up accordingly. So it had to downsize the colony again. And while researchers have talked about a strategic monkey reserve for pandemics, one has never been funded. “There needs to be a real national investment to build the infrastructure, not only for this pandemic, but also for the future with the next pandemic,” says Jay Rappaport, the director of the Tulane National Primate Center.

Meanwhile, China has invested in large monkey-breeding facilities and is a major supplier for the rest of the world. In China, breeding monkeys is cheaper and the animal-rights movement is also quieter. The biopharmaceutical industry in the U.S., in particular, relies heavily on macaques bred in China. The ongoing trade war between the U.S. and China had already made importing monkeys more expensive. Then, when the pandemic hit earlier this year, China stopped exporting them entirely. “I’m not seeing any nonhuman primates moving out of China,” says Matthew R. Bailey, the president of the National Association for Biomedical Research, which advocates for animal research. Industry experts speculate that China, whose scientists are also racing to find COVID-19 treatments, is interested in keeping the animals for its own studies. No one knows when China might start exporting monkeys again.

This reliance on primates from China, Bailey says, is a strategic problem. As primate research becomes harder to do in the U.S., that work may simply get shifted abroad. “Is the American public okay with that? Do we want treatments and cures to be developed here? Or are we okay with them being developed in other countries?” Bailey asks. While many have called for international collaboration in the fight against COVID-19, the pandemic has increased the salience of borders and inflamed “vaccine nationalism,” fears that any country that develops a vaccine first will hoard it for its own citizens.

The current monkey shortage is also forcing scientists to think creatively about how to reduce the number of animals needed for research. For example, says Jeffrey Roberts, the associate director of primate services at the California National Primate Research Center, the different NIH-funded centers are trying to use one group of animals as controls in experiments across different labs. In a typical randomized controlled trial, the control animals are the ones not given the treatment, so they serve as a baseline for comparison. Having the control group and the treated groups in different labs is unusual; to make sure that small changes from lab to lab don’t affect the results, scientists have to be extremely careful to harmonize their protocols. “It’s really impressive,” Roberts says. “I’ve been involved in nonhuman-primate research for 37 years, and I’ve never, ever seen this degree of coordination between different research institutes.”

The shortage is also unlikely to let up soon. Lewis, whose company, Bioqual, has done primate research for several COVID-19 studies, including on Moderna’s vaccine, says that Bioqual was initially able to reuse some animals from non-disease studies. That supply has been used up now; monkeys infected with COVID-19 are euthanized to prevent spread to other monkeys or even potentially humans. The cost of a macaque has since doubled to almost $10,000, according to Lewis. Big companies, he says, which purchase thousands of animals, are also locking out smaller research outfits. And as scientists now try to resume non-COVID-19 research in primates, they’re also contending with delays and much more expensive monkeys. “This may just be the beginning. And I think that we’re all preparing for there to be significant delays,” says R. Keith Reeves, a virologist at Harvard working on HIV.

With so much hope riding on a COVID-19 vaccine, the pandemic has made the stakes of animal research very clear to Americans. Bohm, from Tulane, wonders if, on balance, the pandemic will change how the public views animal research. “I think the answer to the question is yes. In my dealing with neighbors and family and friends, they have a much better understanding of how important animals are to research,” he says. “Whenever a disease affects a family member, people tend to be more supportive of animal research. And in this case, entire communities and families have been affected.” The path back to normal will require a vaccine, and a vaccine will need to be tested first in monkeys.

[xtruss]

A Wave of Graduate Programs Drops the GRE Application Requirement

A Science Careers story from last year looked at why a growing number of science Ph.D. programs are dropping the GRE as an application requirement. Science Mag Archives

— By Katie Langin | May. 29, 2019 | ScienceMag.Org

For decades, one standardized test has been key to admission to U.S. science graduate programs: the Graduate Record Examination (GRE) General Test, a nearly 4-hour marathon of multiple-choice and written questions that test quantitative, verbal, and writing skills. But the long reign of the GRE may be drawing to a close. In response to recent studies showing little correlation between GRE scores and success in graduate school and concern that the test puts underrepresented groups at a disadvantage, a growing number of programs are dropping the GRE as an application requirement.

Science examined Ph.D. application requirements for eight disciplines at 50 top-ranked U.S. research universities. The life sciences have led the so-called GRExit push: In 2018, 44% of molecular biology Ph.D. programs stopped requiring GRE scores. That number will rise to at least 50% for the 2019-2020 application cycle. In neuroscience and ecology, roughly one-third of programs dropped the GRE requirement between 2016 and 2018, and more plan to do so this year. The movement has yet to take hold in some disciplines—more than 90% of the chemistry, physics, geology, computer science, and psychology Ph.D. programs that were surveyed by Science required general GRE scores in 2018. But a few programs in those fields have also joined the exodus.

“It’s such a time of flux right now,” says Joshua Hall, director of graduate admissions for the biological and biomedical science program at the University of North Carolina in Chapel Hill, who keeps a list of life science programs that don’t require GRE scores. A year ago, only a handful of institutions were on his list; now there are 74. One impetus for the change, he says, was a 2017 decision by the University of Michigan’s biomedical sciences graduate program to stop requiring GRE scores in 2018. A few other programs followed, and “as more and more schools dropped it, it created a little bit of a peer pressure situation” because schools worried that they’d miss out on applicants if they required the GRE, Hall says.

GRE supporters say the change is misguided. They say the recent studies that have questioned the GRE’s value are flawed and that it remains a useful predictor. And although schools have other tools for comparing prospective students—such as grades, recommendation letters, and research experience—few are as convenient as the GRE.

“The scores are an easy thing to sort to find people who are plausibly more or less admissible,” which can be particularly appealing for scientists who are accustomed to looking at quantitative data, says Julie Posselt, a higher education researcher at the University of Southern California in Los Angeles who has studied the use of the GRE in admissions. Posselt has also found that many faculty members view GRE scores as a measure of innate intelligence. “They associate a high GRE score with somebody who is more likely to be successful,” she says.

But “those are faculty members’ assumptions,” she emphasizes; the reality is different. For example, Hall authored a 2017 study showing that for 280 graduate students in his program, GRE scores weren’t correlated with the number of first-author papers the students published or how long it took them to complete their degree. A study published in tandem with Hall’s, looking at 495 biomedical Ph.D. students at Vanderbilt University in Nashville, found that applicants with higher GRE scores tended to get better grades in their first-semester grad courses. But GRE scores didn’t predict which students passed their qualifying exams or graduated, how long they spent in the program, how many publications they accrued, or whether they received an individual grant or fellowship. Other recent studies come to similar conclusions.

However, those studies only sampled admitted students, most of whom had relatively high GRE scores, notes David Payne, a vice president at the Educational Testing Service (ETS)—the company headquartered in Princeton, New Jersey, that runs the GRE. “What they don’t really have is the full experiment that you would really, from a scientific research methods perspective, want to do: Randomly admit students over the full range of abilities, as reflected in GRE scores, and see what you find.” Payne argues that GRE scores should be considered as part of a holistic review process. “When programs drop the GRE, they’re throwing out data.”

Others worry that the GRE may hinder diversity and inclusion efforts. ETS data show that women and members of underrepresented racial and ethnic minority groups score lower on the GRE than white men and Asian men do. (ETS argues that this reflects educational background and unequal access to opportunities, not bias against these groups per se.) Paying for training and taking the test—which costs $205 a pop, plus travel in some cases—can be a burden for low-income students. The timed test can also present a challenge for students who don’t speak English as a first language.

Payne and others argue that scoring well on the GRE can help students who might otherwise go unnoticed, including students who had fewer opportunities because of structural disadvantages. But GRExit proponents disagree. “The problem with looking at a strong GRE score is you don’t know what the student did to get that score,” such as whether they took the test many times, says Linda Sealy, director of the Initiative for Maximizing Student Diversity at Vanderbilt University. “Having a high GRE score alone shouldn’t necessarily be a factor that pushes someone over the edge for a Ph.D. program,” agrees Hall.

Dropping the GRE “just seems like a no-brainer,” says Arthur Kosowsky, chair of the physics and astronomy department at the University of Pittsburgh in Pennsylvania, which eliminated the GRE requirement in 2018. “This test is both not really measuring something useful … and at the same time discriminating against students who we are trying to work very hard to increase the numbers of in our program.”

Many Ph.D. programs that have dropped the requirement give students the option of submitting GRE scores, but Posselt recommends against that approach. Applicants who submit GRE test results will, on average, have higher scores, and “this might skew the way that faculty look at people who don’t submit scores,” she says. Programs should “either look at scores or don’t look at scores.”

Whether dropping the GRE requirement will diversify applicant pools is far from certain. But Jon Gottesman, director of the Office of Biomedical Graduate Research, Education and Training at the University of Minnesota Medical School in Minneapolis, hopes to find out. He and his colleagues sent out a survey to biomedical graduate programs last month, asking for information about their admissions process and data on their applicant pools, such as the total number of applicants and the percentage from underrepresented groups. “We’ll have to see,” he says. “I have a feeling we’re going to have to be looking at this for more years to really get a sense.”

— Katie Langin is the associate editor for Science Careers

[kansascityhappenings]

Half of America will be obese within 10 years, study says, unless we work together

If America does not collectively adopt healthier eating habits, over half of the nation will be obese within 10 years.

Even worse, one in four Americans will be “severely obese” with a body mass index over 35, which means they will be more than 100 pounds overweight.

That alarming prediction, published Wednesday in NEJM, was the result of a study analyzing self-reported body mass index (BMI) data from over six million American adults.

Half of the nation will be obese within 10 years, according to a study published Wednesday in NEJM.

Considering the challenges of battling weight loss, that’s devastating news for the future health of our nation.

“Given how notoriously difficult obesity is to treat once it’s established, you can see that we’re in an untenable situation,” said Aviva Must, chair of Tufts University’s Public Health and Community Medicine, who was not involved in the study.

“The societal cost is high,” she said, “both in terms of obesity-related health consequences and healthcare expenditures which could bring us to our knees.”

Startling state-by-state data

One of the first research efforts to drill down to the state level, the study found that 29 states, mostly in the South and Midwest, will be hit hardest, with more than 50% of their residents considered obese.

But no part of the country is spared — in all 50 states, at least 35% of the population will be obese, the study found.

“What’s even more concerning is the rise in severe obesity,” said lead author Zachary Ward, an analyst at Harvard Chan School’s Center for Health Decision Science.

“Nationally, severe obesity — typically over 100 pounds of excess weight — will become the most common BMI category,” Ward said. “Prevalence will be higher than 25% in 25 states.”

Currently, only 18% of all Americans are severely obese. If the trend continues, the study said, severe obesity would “become as prevalent as overall obesity was in the 1990s.”

The study also found certain subpopulations to be most at risk for severe obesity: women, non-Hispanic black adults and low-income adults who make less than $50,000 per year.

“And we find that for very low-income adults — adults with less than $20,000 annual household income — severe obesity will be the most common BMI category in 44 states,” Ward said. “So basically everywhere in the country.”

What happened?

“Fifty years ago, obesity was a relatively rare condition,” Must said. “People who were poor were underweight, not overweight. But that has changed.”

One reason is the rise of sugar-sweetened beverages and ultra-processed foods, which contribute calories but little nutrition. Another is that the price of food, including unhealthy fast food choices, has fallen in America when you adjust for inflation.

“Low food prices are certainly part of it,” Must said. “Also limited options for physical activity. And there’s a lot being written about the stress of structural racism and how that influences people’s behavioral patterns. So it’s very complicated.”

Can we fix it?

“There’s no rosy picture here, but I don’t think we can throw in the towel,” Must said. “It will probably take lots of federal, state and local policy interventions and regulations to have a big impact. We can’t rely on individual behavior change in an environment that is so obesity promoting.”

Studies have shown some promising tactics, she said: bolstering local public transportation systems to encourage walking instead of driving; keeping schools open on weekends and during summers to allow access to gyms and swimming pools; and increasing support for farm-to-school and farm-to-work food programs, as well as farmers’ markets, to boost access to low-cost fruits and vegetables.

Other interventions include calorie labeling on restaurant and drive-thru menus and replacing vending machines with smart snacks in schools.

“We’ve also looked at eliminating the tax deduction businesses get for advertising unhealthy foods to children,” Ward said. “The money that they spend on advertising foods can basically be written off as a tax deduction.

“That could be one reason why we see such disparities by race, ethnicity or income,” Ward said, “because companies are directly targeting advertising at these groups.”

In a prior study, Ward and his team at Harvard found that three interventions saved more in health care costs than the price to implement them: elimination of the tax deduction on advertising; improving nutrition standards for school snacks; and imposing an excise tax on sugary beverages.

The most cost effective solution was the tax on sugar-sweetened beverages. The study found the tax saved $30 in health care costs for every dollar spent on the program.

“So much added sugar is delivered through sugar-sweetened beverages, and people do have other options for hydration,” Must said. “I think it’s an easy target.”

But not necessarily a popular one. Still, the complexity of the problem means that a solution will truly take a village, experts say, with every American doing their part.

“I don’t think it’s impossible,” Must said, pointing to a slowing of the obesity rate in children in America. That trend is the result of interventions in school lunches; snack programs; and a change in the nutritional allowances in the Special Supplemental Nutrition Program for Women, Infants and Children, which helps feed more than seven million pregnant and postpartum women and children until age five.

In 2009 the program decreased the intake of foods and beverages associated with excess weight gain. By simply cutting the juice allowance in half, reducing cheese, requiring whole grain products and requiring low-fat or skim milk, a study found the program reduced the obesity rate in children between two and four years of age and boosted the intake of fruits and vegetables.

That is certainly a model for future attempts among both children and adults, Ward said, adding that if Americans could just keep their current weight instead of gaining, the trends could be reversed.

“It’s really hard to lose weight,” Ward said. “It’s really hard to treat obesity. So prevention really has to be at the forefront of efforts to combat this growing epidemic.”

from FOX 4 Kansas City WDAF-TV | News, Weather, Sports https://fox4kc.com/2019/12/19/half-of-america-will-be-obese-within-10-years-study-says-unless-we-work-together/

from Kansas City Happenings https://kansascityhappenings.wordpress.com/2019/12/19/half-of-america-will-be-obese-within-10-years-study-says-unless-we-work-together/

[hollywoodjuliorivas]

mo

How to make your firm more diverse and inclusive

Tips for chief executives

Print edition | Business

Nov 7th 2019

To: ceo

cc: pa

Subject: A hard-headed guide to corporate diversity

Dear David,

You face pressure to “do something” about diversity in your company—not only from your wife and woke children. Corporate clients increasingly demand it in your supply chain. Regulators, who use a “stable” or “inclusive” culture as a proxy for low risk, are breathing down your neck. Governments like Britain’s, which now mandates pay-gap reporting, insist on making more of your sensitive data public. And employees, including former ones, can air their complaints on social media.

Small wonder that 87% of your fellow bosses told consultants at pwc that diversity is a business priority. I’m sure you did, too. After all, you recently posted a job opening for a diversity manager. You were not alone; the number of such offers in Britain has doubled in the past year, say analysts at Glassdoor, a recruitment website. Since June 2017 more than 800 American ceos have signed a pledge to “advance diversity and inclusion in the workplace”.

That is where we are: lots of talk, plenty of initiatives, little change on the ground. Between 2015 and 2018 the share of female executives at large (mostly) American and British firms went from 12% to 14%; for ethnic minorities it moved from 12% to 13%. The ftse 100 has fewer female ceos (six) than it does bosses who share your name (seven). In American companies with over 100 employees, the share of black men in management was 3.4% in 2017, half their share in the population as a whole—and virtually unchanged from 3% in 1985. White women make up 25% of executives and senior managers, compared with 60% for white men. Something is clearly amiss.

In the past this letter would have gone straight to your legal department. Since the term “diversity” entered the corporate lexicon in the 1960s it has been code for avoiding lawsuits—especially in America, where companies have coughed up billions in fines for discrimination over the years. The financial sector still treats it mostly as a compliance issue.

Now you are no doubt tempted to forward it to someone in hr, almost certainly a woman with an arts degree, a sound moral compass and too little power. Don’t. This is your problem. Without your leadership it is unlikely to be solved soon.

Keep reading

Deep inside, you may be wondering if anything really needs solving. The short answer is: it does. With that in mind, you should ask yourself three things.

First, why does diversity matter to your firm? Is your reputation in trouble, as it was for Uber, Nike, Lloyd’s of London and others scarred by #MeToo? Do you, like consumer giants such as p&g, hope that more diversity makes for better products? Are you concerned about attracting and retaining bright sparks? You would be in good company: 97% of executives fret about increased competition for talent (according to Mercer’s hr consultants).

Or are you hoping that diversity will boost the bottom line? To be perfectly honest, I have no idea if it does. It is hard to tell if diversity helps firms do well, or if successful firms are also more enlightened on other matters. But variety has been linked to innovation, productivity and, for example in diverse teams of surgeons, fewer mistakes. Lack of it breeds groupthink—which in turn can lead to disasters. The Bay of Pigs invasion and the Lehman Brothers collapse stemmed from narrow-mindedness. And employees who believe their firm cares about gender diversity are 40% more likely to be satisfied at work—and possibly more productive as a result.

Once you have sorted out the why, consider where you want to get to. Some firms, like Facebook, Nike or p&g, say they wish to mirror their customer base. Others are keen not to recruit from an artificially thin talent pool. Goldman Sachs claims its new entry-level recruitment targets—50% female and, in America, 14% Hispanic and 11% black—are based on things like graduation rates. Clear goals make it easier to assess if you are on track. But make them attainable. Qantas’s goal of 40% of its pilot intake to be female by 2028 is as admirable as it looks unrealistic: today just one in 20 pilots worldwide is a woman.

The third question concerns barriers that stop diverse talent from flourishing at your firm. Mapping how it flows through your organisation and where the blockages and leaks happen is a start. A McKinsey study of more than 300 companies identified the second step of the career ladder, from entry level to manager, as the “broken rung”: for every 100 men only 72 women (and just 68 Hispanic and 58 black ones) earned that critical early promotion. When Google was losing women in disproportionate numbers it homed in on maternity as the principal cause; the technology giant increased maternity leave and support for mothers returning to work.

Staff surveys can help, provided they are large and comprehensive enough. After its #MeToo moment, Lloyd’s, an insurance market, found that 45% of staff felt unable to raise concerns about improper conduct. Employees are now encouraged to speak up, including through a bullying-and-harassment helpline. A “culture dashboard” tracking progress on survey metrics will be published with the Lloyd’s annual report.

Now you’ve got your diversity-and-inclusion priorities straight and diagnosed what needs fixing. Good. Before you order a rainbow float for a Pride parade and send staff on a micro-aggression avoidance course, here is what not to do.

American firms spend billions a year on training. Half of large ones have unconscious-bias seminars. Most of these “d&i” programmes are a waste. Or worse: recent research from America shows that diversity statements can put off minorities, possibly because they perceive them as tokenism. Often, firms do d but forget i, which is about ensuring that the workforce is not just diverse, but thriving. Too many try to fix people instead of procedures. Training women to be more assertive in asking for a promotion or pay rise is pointless; they are just as likely to ask for these but also likelier to be seen as pushy when they do. Ushering your managers onto the “Check Your Blind Spots bus”, currently touring America as part of the ceos’ drive, is unlikely to do much. “Days of understanding”, popular in American offices, risk causing “diversity fatigue”. It is hard to beat bias out of individuals—easier to root it out of systems.

The don’ts

Take Silicon Valley. Big Tech has splurged on d&i to little effect. Representation of blacks and Hispanics has been flat (see chart). Girls Who Code, an industry-sponsored ngo, found that a quarter of young women who applied for internships at tech firms said they were asked inappropriate or biased questions. Others reported being flirted with or demeaned. It’s no use hiring diverse coders if the message then is: wear a hoodie and pretend to be a guy, or this is no place for you. They will underperform—or flee, leaving you as undiverse as before. Firms that do not change their ways beyond recruitment see high attrition rates of diverse talent. A lack of diversity is a symptom of deeper problems that a few diversity hires won’t mend.

At this point the how should be relatively clear. In a nutshell, it is all about creating a level playing field. When recruiting, software can mute biases by concealing giveaways to a candidate’s gender or ethnic identity. These include names but also less obvious hints like the sports they play. If only the usual suspects apply, look harder. Specialised recruitment drives, such as visiting “black” colleges or advertising in women’s forums, appear to work. The Bank of England no longer visits the Russell group of top universities, whose graduates apply in spades anyway, and focuses instead on less elite schools. bhp, an Anglo-Australian mining giant, broadened its search for female miners by recruiting from professions, such as nursing, with some similar skills.

In an effort to find trainees from different backgrounds, British law firms are trying “contextual recruitment”. An applicant with Bs from a school where everyone got Cs may be more impressive than one with As from a place full of A* pupils. Rare, a recruitment firm, has developed software which screens candidates for disadvantage and gauges their outperformance against the average for their school.

Once in the workplace, the clearer your criteria for professional advancement, the better. Informality is the enemy of women and minorities. It perpetuates bias. Surveys of American engineers and lawyers found that female workers were nearly twice as likely as their male peers to be saddled with “office housework”, like setting up meetings and conference calls. White men were likelier to be given careerenhancing tasks such as client meetings.

Sponsorship schemes are an effective way to ensure traditionally sidelined groups get a fair shot. PayScale, a pay-comparison site, found that employees with a sponsor made 11.6% more than those without. The Bank of England has offered most of its sponsorship places to ethnic-minority women. Staff surveys, if bite-sized but regular, can bring clarity to fuzzy inclusion metrics. “Psychological safety”, lingo for an environment where people feel free to speak their mind, can be tracked with questions like “are your ideas regularly attributed to someone else?” or “are you regularly interrupted in meetings?” Rotating who chairs a meeting, or a firm word with loudmouths who dominate it, can help.

Many employers—yourself included—would be horrified to learn that they implicitly require employees who want to be considered leadership material to adjust their behaviour. Women shouldn’t need to “act like a man”, gay employees to “act straight” or people with frizzy hair to treat it to “look professional” (ie, white). Let grievances fester and your workers will lose motivation or simply leave.

That is a lot to take in. But unless you do, your most valuable resource—workers—will not be as good as it could be. Best to get ahead of the problem. It isn’t that hard. And it can pay off mightily.

Yours,

Shareholder■

[moredickpics-blog]

Men Who Send Unsolicited Dick Pics Are Bigger Narcissists, Study Finds

The dick pic; so widely disseminated—yet so universally scorned. How many message threads end abruptly after an unwitting recipient lays eyes on a glaring, one-eyed schlong? From Weinergate to Tony Clement; the urge to send dick pics is apparently so compelling that caution is thrown to the wind, even when the personal, social and political ramifications are enormous.

These lewd dispatches are rampant (half of all women between 18-36 reported on having received one), but those who openly admit to sending them are few and far between. And while many women rightly view this as a form of harassment, it does not appear that dick pic senders see it that way—often slapping the lurid photos into otherwise benign conversation. Are they desperate? Do they do it for validation? Shock? Thrills? Comic relief? Or is there something darker at play? Beyond a painful inability to read the room; what is their deal? Why do men do this?

Thankfully, a new study presented at the Society For The Scientific Study of Sexuality in Montreal last November, has suggested some answers. It is believed to be the first empirical investigation of its kind into the phenomenon of the dick pic, drilling down to unearth the reasons why straight men send unsolicited pictures of their dicks.

More than 1000 self-selecting straight men, ages 16 to 75, were recruited from various social media sites, a university-based research participant pool and Amazon Mechanical Turk to take part in the study. They were measured on levels of narcissism, exhibitionism, benevolent and hostile sexism, and endorsement of sexual behaviors—basically to ascertain if they were oversexed. They were asked about their motivations, and what they hoped the outcome would be. Nearly half (48%) of those surveyed admitted to having sent an unsolicited dick pic in the past. The majority of the dick pic-senders were white, married or in a serious relationship, had some college/university education, and the average age of the sender was 31 (The average age of the non-sender was 33, however, so it doesn’t appear as if age is a factor).

“In a nutshell,” study lead Dr. Cory Pedersen, of Kwantlen Polytechnic University, said,

“men who had reported having sent unsolicited dick pics showed higher levels of narcissism relative to men who had never sent such images. They also demonstrated higher levels of both hostile (overtly negative views of women) and benevolent (woman-on-a-pedestal) sexism.”

They were also measured on their opinions around sexuality, based on hypothetical musings that men who send dick pics must be oversexed. “There was no difference between the two groups in the extent to which they watched porn, or masturbated or fantasized,” says Pedersen. “The dick pic-ers were not more ‘sexual’ in nature.”

Additionally, they were measured on misogyny ( Do you send these images because you dislike women), public exhibitionism (Have you ever exposed your genitals to someone that you know but who didn’t ask you to in a public setting?) and sexual satisfaction ( I send these pictures and then I can masturbate knowing that a woman is looking at a picture of my dick). “There was some endorsement for all of those other categories,” says Pedersen, “but they were very low.”

Pedersen honed in on two major reasons why men are motivated to do this. The first was a transactional mindset; they send these images in the hope that they’ll get some nudes in return. Or, fingers crossed, it will lead to a RL hookup. “The second most popular reason was what we called partner hunting,” says Pedersen. “They believe sending dick pics is an appropriate form of flirting with someone, this is how you let someone know that you’re interested in them, that you’re attracted to them. That you want to have a connection with them.”

When asked what they were hoping to get out of sending these images, a whopping 82 percent of respondents were hoping to make the person who received the image feel “sexual excitement .” “This is quite contrary to the popularly endorsed belief that men send these pics hoping to get shock,” says Pedersen. “They believe they’re going to turn someone on. The top three hoped-for reactions were positive; men were hoping for sexual excitement from the part of the recipient, they hoped the recipient would feel attractive, and they hoped the recipient would feel valued.” Given the #MeToo climate we find ourselves in, this obliviousness is astonishing. The individuals sending these unsolicited photos could stand a dose of empathy—and a clue.

Pedersen agrees there’s likely some projection at play; that’s how they would feel if they received a nude photo from a woman. “I would hypothesize it would only take one or two positive endorsements; ‘Hey! That’s a nice dick!’ for that to be reinforcing enough to continue that type of strategy,” Pedersen said. “Humans are prone to pay attention to things we already believe to be true, and to ignore things that disabuse us of our ideas. If we get one positive endorsement we think; hey, this is working! We ignore all of the women who reply with you’re gross.”

“While we do not dispute or deny that consent is sexy, and that it is an important part of all sexual interactions, our data suggests that the large majority of men are not sending these images because they hate women, or because they want power or control,” says Pedersen. “That runs contrary to a lot of feminist discourses that men do this because they hate women; that is not what we found.”

This, in and of itself, is kind of enheartening. “It runs contrary to our popular culture’s views on this subject. Nonetheless, no matter what anyone takes from this information; consent is sexy. if somebody wants to see your penis, they will probably let you know.”

https://www.vice.com/amp/en_ca/article/7xgaje/men-who-send-unsolicited-dick-pics-are-bigger-narcissists-study-finds

[wireghana3-blog]

Persistent Inequity & Dangerously Ignorant Denial

Another excerpt from forthcoming work:

======================

In 2011, the Obama administration formed a national equity commission[1] to explore fiscal inequities across U.S. Schools. In one meeting of that commission, participant Eric Hanushek introduced the following table (A-36-1, in Figure 44) from the National Center for Education Statistics to assert that, on average, U.S. States had already raised levels of spending in high poverty districts to the point where, on average, high poverty districts spend more than low poverty districts.  This statement is factually correct, based on Table A-36-1 of the 2010 Condition of Education Report, of the National Center for Education Statistics. The implication being that school funding equity is not the problem, but rather, the problem lies with inefficiency in high poverty districts.

Figure 1

There are a few problems with using this table to draw these implications, setting aside that the dollar figures are not adjusted for differences in labor costs across settings.  While $10,978 (constant dollars) is in fact higher than $10,850, this difference is hardly enough to provide for the differences in programs and services needed to close achievement gaps between our highest and lowest poverty children. But perhaps most importantly, these broad, national average figures hide substantial variation both across and within states. Many states have highly inequitable school funding systems and many districts and the children they serve continue to be significantly disadvantaged by state school finance systems, ranging from imperfect to god-awful.

In 2014 I produced a report for the Center for American Progress identifying America’s Most Financially Disadvantaged School Districts.  This report came about as an extension of a series of blog posts in which I had identified what I referred to as America’s Most Screwed School Districts.  It had become increasingly clear to me that the indicators we created for the School Funding Fairness report card, while useful for describing overall patterns, were hiding important disparities within states behind the averages. For example, the disparities I pointed out in the previous section in Massachusetts and New Jersey. These are two of the best, most progressive state school finance systems in the nation, but even in these states there are districts which are high in student poverty and have far fewer resources than the other districts around them. Many districts, and thus the children they serve, were being overlooked in our indicators and subject to mischaracterization by others, without readily available rebuttal.

It is important to understand that the value of any given level of education funding, in any given location, is relative. That is, it does not matter whether a district spends $10,000 per pupil or $20,000 per pupil. It matters how that funding compares to other districts operating in the same regional labor market—and, for that matter, how that money relates to other conditions in the regional labor market. The first reason relative funding matters is that schooling is labor intensive. The quality of schooling depends largely on the ability of schools or districts to recruit and retain quality employees. The largest share of school districts’ annual operating budgets is tied up in the salaries and wages of teachers and other school workers. The ability to recruit and retain teachers in a school district in any given labor market depends on the wage a district can pay to teachers relative to other surrounding schools or districts and relative to nonteaching alternatives in the same labor market.[2] The second reason is that graduates’ access to opportunities beyond high school is largely relative and regional. The ability of graduates of one school district to gain access to higher education or the labor force depends on the regional pool in which the graduate must compete.[3]

Table 1 lists k-12 (unified) districts identified based on 2015 fiscal and poverty data, which have <90% state and local revenue of their labor market average and >150% of the poverty rate.  Many other repeat suspects like Philadelphia (w/approximately 90% revenue) continue to lie at the margins. Year after year, Philadelphia and Chicago have appeared as the two most screwed large urban districts. Along with Philadelphia, other Pennsylvania cities including Reading and Allentown face even more dire conditions, and along with Chicago, Illinois districts like Waukegan and Joliet make the list year after year.  While Hartford and New Haven in Connecticut have received additional aid in support of their magnet programs, creating an appearance of progressive funding in Connecticut, other districts including Bridgeport, Waterbury and New Britain have been entirely left out. It seems a relatively easy call to suggest that disparities of this type and magnitude are simply wrong – unfair – and should be remedied.

Table 1

America’s Most Financially Disadvantaged Districts 2015

Baker, B.D., Srikanth, A., Weber, M.A. (2016). Rutgers Graduate School of Education/Education Law Center: School Funding Fairness Data System. Retrieved from: http://www.schoolfundingfairness.org/data-download

To put these disparities into context, we know that high poverty districts need not only equal resources but substantially more resources per pupil to achieve common outcomes for their students. One of the more rigorous studies to ask just how much more applied cost models to districts in New York state, finding that the costs associated with each additional child in poverty (U.S. Census poverty income level) were about 1.5 more (2.5 times) the costs of achieving the same outcome measures for children not in poverty.[4] Thus, a district serving 30% children below the poverty line would have costs approximately 75% higher or 1.75 times (.3 x 2.5) per pupil cost for a district with 0% census poverty.

As obviously problematic as these disparities are, they still have their detractors and deniers, which is especially disheartening. Take for example the twitter exchange below between Andy Smarick, Fellow of the American Enterprise Institute, later appointed President of the Maryland State Board of Education and Author of The Urban School System of the Future[5], and Kombiz Lavasany, a research manager at the American Federation of Teachers.  The premise of Mr. Smarick’s book is that urban school systems have failed despite receiving massive resources. According to Mr. Smarick, urban traditional public school districts don’t and can’t work, and must be replaced with a portfolio of privately managed autonomous charter schools. This premise is largely borrowed from a 1997 book by Paul Hill, Lawrence Pierce and Jim Guthrie titled Reinventing Public Education.[6]

In the exchange below, Andy Smarick opines with great confidence that Philadelphia is among those large urban districts which have received massive sums of money, repeatedly, to “prop it up.”[7] The only hint at evidence here is the claim that Philadelphia’s state aid is among the highest in the state. Of course, that’s because Philadelphia is by far the largest district in the state (several times larger than any other district).

Figure 2

I might have taken less offense to Mr. Smarick’s proclamation had I not been under the false impression that most reasonably informed education policy wonks understood that Philadelphia was in fact one of (if not the) nation’s least well-funded large urban districts, operating in the context of one of the nation’s least equitable states. Apparently, it wasn’t so widely understood. Nonetheless, publicly available and easily fact-checkable data were and are pretty clear on this point.

Let’s take a look at Pennsylvania school finance and the position of Philadelphia within that mix. Figure 3 shows Pennsylvania school districts arranged by their poverty rates and by per pupil spending relative to districts in their surrounding labor market.  Again, the size of each circle represents the enrollment size of each district.  Philadelphia stands out as the large circle in the lower right area of the graph. That is, Philadelphia has a little more than double the poverty rate of all districts in its area, and has less than 80% of the current spending per pupil in 2015.  In other words, Philadelphia is the classic case of a “Screwed District” as I originally reported on my blog in June of 2012.[8]

Figure 3

Baker, B.D., Srikanth, A., Weber, M.A. (2016). Rutgers Graduate School of Education/Education Law Center: School Funding Fairness Data System. Retrieved from: http://www.schoolfundingfairness.org/data-download

Figure 4 shows the plight of Philadelphia Public Schools over time, from 1993 to 2015.  During this period, child poverty rates climbed from just under double the labor market average to over double the labor market average.  Throughout the period of over two decades, Philadelphia has received substantively less in per pupil revenue and spent less per pupil on average than surrounding districts, despite having much greater need and facing much higher costs.  Despite bombastic rhetoric to the contrary, the Commonwealth of Pennsylvania has done little, if anything, for decades to “prop up” school spending in Philadelphia.  Evidence-free bluster to the contrary is reckless and irresponsible.

Figure 4

Baker, B.D., Srikanth, A., Weber, M.A. (2016). Rutgers Graduate School of Education/Education Law Center: School Funding Fairness Data System. Retrieved from: http://www.schoolfundingfairness.org/data-download

Among the financially disadvantaged districts of the Commonwealth, are two other eastern Pennsylvania cities – Reading and Allentown.  Reading was the subject of a feature article in the Huffington Post by education writer Joy Resmovits back in 2012, in which Resmovits detailed the ground level impact of Reading’s funding plight, including substantial staffing cuts and elimination of the district’s preschool program.[9] Kansas City native Michael Q. McShane, then with the American Enterprise Institute (now with the Missouri-based Show-Me Institute) responded to the Resmovits column in a piece he titled “It’s not about the money” in which he argued: “Ms. Resmovits was right to point to Reading as an example of a property-poor district that cannot raise enough local funds to support education. However, as the 20-year changes in funding show, the state has worked to remedy this shortfall.”[10] McShane’s evidentiary basis for his claim was to show that the percent of Reading’s funding coming from the state had increased over time and was greater than that of other districts. Thus, the state was doing its part and responsibility for any failures should fall squarely on Reading school district officials. Clearly, however, as shown in Figure 5, the state’s efforts have been far from sufficient to remedy the shortfall.  The percent of revenue that comes from the state is irrelevant if the sum of state and local revenue remains insufficient. Reading is an especially flagrant case of savage school funding inequalities. Reading is a mid-size city district with nearly 250% of the poverty rate and about 73.6% of the state and local revenue per pupil of the surrounding labor market.

Figure 5

Baker, B.D., Srikanth, A., Weber, M.A. (2016). Rutgers Graduate School of Education/Education Law Center: School Funding Fairness Data System. Retrieved from: http://www.schoolfundingfairness.org/data-download

While Philadelphia and Reading are particularly egregious examples of disparities, it is false to assume or make data-free proclamations regarding propping up large city school districts with vast sums of state aid. Figure 6 shows the relative poverty and relative state and local revenue for large city school districts with 50,000 or more students in 2013.  Again, Philadelphia and Chicago are most disadvantaged. Boston is most advantaged here, but its margin of poverty difference is still double that of its surroundings and margin of revenue difference only about 30% higher than surroundings.  Even Boston’s progressive spending differential falls well short of cost estimates for achieving common outcomes.[11] Thus it should come as no surprise that Boston students’ outcomes continue to fall short.

Figure 6

Baker, B.D., Srikanth, A., Weber, M.A. (2016). Rutgers Graduate School of Education/Education Law Center: School Funding Fairness Data System. Retrieved from: http://www.schoolfundingfairness.org/data-download

NOTES

[1] Mercury News. A 28-member commission studing the problem of school fundign inequities, will hold a meeting in San Jose March 4. Feb 24, 2011. http://www.mercurynews.com/2011/02/24/a-28-member-commission-studying-the-problem-of-school-funding-inequities-will-hold-a-meeting-in-san-jose-march-4/

[2] Bruce, D. B. “Revisiting the Age-Old Question: Does Money Matter in Education.” The Albert Shanker Institute (2012).

& Baker, Bruce D. “Does money matter in education?.” Albert Shanker Institute (2016).

http://www.shankerinstitute.org/images/doesmoneymatter_final.pdf.

[3] Bruce D. Baker and Preston C. Green III as well as William Koski and Rob Reich explain that to a large extent, education operates as a positional good, whereby the advantages obtained by some necessarily translate to disadvantages for others. For example, Baker and Green explain that, “In a system where children are guaranteed only minimally adequate K–12 education, but where many receive far superior opportunities, those with only minimally adequate education will have limited opportunities in higher education or the workplace.”

Baker, Bruce, and Preston Green. “Conceptions of equity and adequacy in school finance.” Handbook of research in education finance and policy (2008): 203-221.;

Koski, William S., and Rob Reich. “When adequate isn’t: The retreat from equity in educational law and policy and why it matters.” Emory LJ 56 (2006): 545.

, available at http://www.law.emory.edu/fileadmin/journals/elj/56/3/Koski___Reich.pdf.

[4] Duncombe, William, and John Yinger. “How much more does a disadvantaged student cost?.” Economics of Education Review 24, no. 5 (2005): 513-532.

[5] Smarick, Andy. The urban school system of the future: Applying the principles and lessons of chartering. R&L Education, 2012.

See also: Wexler, Natalie. Should we give up on urban public school districts and replace them with something completely different? Greater Greater Washington. May 7, 2014. https://ggwash.org/view/34640/should-we-give-up-on-urban-public-school-districts-and-replace-them-with-something-completely-different

[6] Hill, Paul, Lawrence C. Pierce, and James W. Guthrie. Reinventing public education: How contracting can transform America’s schools. University of Chicago Press, 2009.

[7] Smarick mentions Baltimore, Boston, Detroit, Milwaukee and New York in an exchange here: https://edexcellence.net/articles/does-money-matter-is-school-funding-fair

[8] Baker, Bruce D. America’s Most Screwed City Schools. School Finance 101. June 2, 2012. https://schoolfinance101.wordpress.com/2012/06/02/americas-most-screwed-city-schools-where-are-the-least-fairly-funded-city-districts/

[9]Resmovitz, Joy. Reading, Pennsylvania: Poorest U.S. City Loses Pre-Kindergarten, 170 Teachers. Huffington Post. June 15, 2012.  http://www.huffingtonpost.com/2012/06/14/reading-pennsylvania-schools_n_1598398.html

[10]McShane, Michael Q. Fact Checking HuffPost: It’s not about the money. American Enterprise Institute. Oct 5, 2012.  https://www.aei.org/publication/fact-checking-huffpost-its-not-about-the-money/

[11] Duncombe, William, and John Yinger. “Why is it so hard to help central city schools?.” Journal of Policy Analysis and Management (1997): 85-113.

Duncombe, William, and John Yinger. “How much more does a disadvantaged student cost?.” Economics of Education Review 24, no. 5 (2005): 513-532.

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Source: https://schoolfinance101.wordpress.com/2017/10/19/persistent-inequity-dangerously-ignorant-denial/

[squirrelsave]

Smart Investing with Global Diversification at SquirrelSave

Internet social media has shifted the way news or facts are delivered and perceived — with profound implications for the way we should invest.

I am asked by many these days about the implications for their investments because of the news frenzy about the USA-China trade war. I can understand the anxiety. Yet, I need to remind ourselves about our human short-term memories.

There are so many other issues that matter, but we focus on is what is currently topical — and ironically, not necessarily relevant. As emotional humans, we tend to focus on what we worry about — especially if others we interact with have the same anxieties. We tend to group ourselves with others who share the same emotional tendencies. Quite understandable. However, there is a bigger picture at stake.

What we perceive as an individual or a cohesive group of individuals may block out relevant facts or possibilities.

These days, the internet-driven social media phenomenon has simply accelerated the effects of opinion-making and responses, even by governments — with profound changes in the political landscape. But that’s another topic.

In the investment world, those of us who follow economics and investment news will tend to read from the same broad “trusted” sources. In the days when news followed the human cycle of facts collection, writing, editing, vetting, publishing and distribution to your doorstep or newsstand every 12 or 24 hours, decisions could be made with more deliberation. These days, with the internet platform of instant information, as distinct from facts or even news, anyone can influence others in an instant and at a click. Surely, investment markets as we know them today have become more correlated without a master conductor. Indeed, they have.

All you have to do is observe the wild swings in investment markets from New York to Tokyo. As if fish swimming in shoals, funds ebb and flow in “risk-on, risk-off” pendulum fashion — exacerbating sharp swings in global investment markets. This is the reason why active or “alpha” managers have fared poorly and stock-pickers or value investors (like I was once) are flummoxed by stocks rising and falling in the same waves.

Of course, anyone can cite at least one active manager who has done well. But that’s not the whole truth. Even the alpha manager who claims the trophy is nervous that the next winner is not likely to be the same. They know truthfully without shouting it out, that the evidence shows that no single winner can win consistently. “Chance” and “luck” are words they detest — preferring “skill” and “experience”. Yet, many more active managers have lost despite skills and experience. The truth is always hard to swallow.

Rising market correlation is making it difficult to squeeze out alpha returns.

It used to be easy when information flowed slowly — so that a few can capitalise on the time gap before others realised what the information meant for investments. I know. I was once an investment analyst seeking out information and knowledge with time to analyse and communicate to clients before others. Now, that time advantage has been wiped out by the internet. Investment markets tend to move nowadays with alternating cycles of greed and fear-driven mainly by short-term sentiment about the direction of the global economy and little else.

This explains why I get so many questions about the same topic — and the same topic changes in almost orchestrated unison every time the social media headlines shift focus.

Heightened market correlation is the enemy of alpha seeking managers.

So as an investor, one should acknowledge the truth and adopt a more relevant investment strategy to recognise that markets are swinging up and down between two fat tails of long-run returns.

Why? Technology-driven high-frequency trading and the massive inflow of funds into index-based products such as Exchange-Traded Funds (ETFs) has probably contributed to the increased market correlations across the world. ETF creation and redemption form a one trillion US dollar market today. The buying and selling of all index constituents tracked by the ETFs suggest that stock prices move more closely together.

A study by Professor Jeffrey Wurgler of New York University for the USA National Bureau of Economic Research shows how the simple inclusion of stocks in specified benchmark indices profoundly affects the stocks’ performance to the extent that they move in tandem with other index members irrespective of differences in their earnings or relative valuations. The study found that, on average, the share prices of stocks added to the S&P 500 between 1990 and 2005 increased almost 9 per cent upon their inclusion, with the effect rising over time because of more inflows into the index fund. Conversely, stocks deleted from the S&P 500 index tumbled by even more. This supports the school that argues for index-linked investing as a better investment strategy. And the market is voting with trillions of dollars flowing from active to passive funds.

Other reasons cited for increased market correlation is the globalisation of financial markets and economic interdependencies. Markets are less nationalistic than the post-cold war era with global and multinational companies listing in stock markets different from their original nationalities.

What you can do in response to heightened market correlation is to take a longer-term view of the market.

Short term investing to squeeze returns is more like betting. So you need to know your risk appetite and your more-like-betting capacity to take on short term betting risks. For those who truly want to invest, you need to ask yourself if you can really track, monitor and predict risks when information now flows too fast for human analysis and action.

Besides taking a longer-term view, you should manage risks by focusing on diversification instead of trying to pick winners.

As swings in markets can be pronounced due to heightened market correlation, diversification can mitigate volatile and unpredictable markets.

In the past, as a stock picker, I could “diversify” by betting on a pool of 10 to 20 stocks. But I would not be able to track stocks beyond my geographic knowledge and sleeping time zone! So my clients were constrained by my human limitations. Nonetheless, every competitor faced the same constraints

By diversifying to hold a spread of investments that are likely to react differently to the same market or economic conditions, you reduce the chances of your investment portfolio taking a big hit when markets swing one way or the other.

If your investment portfolio is likened to a pizza, diversification is akin to assembling a pizza with different flavoured slices and varying the size of each slice. Do review our video about SquirrelSave and the pizza analogy.

Today, machine learning artificial intelligence is at our disposal — thanks to the ready availability of real-time data.

Yet few traditional investment managers are changing their old ways. Quite understandable when we see how old they are and how humans are resistant to change — especially when the clients are also unaware of new possibilities.

The evidence is clear. If the market is enjoying a bull run as a wave, how smart does an investment manager have to be? It is when the market is in a bear phase, that the truth and fallibility of human investment managers become clear. I hope you don’t have to experience that first-hand.

In the face of heightened market correlations, you should use artificial intelligence and machine learning to invest smarter.

Thanks to the combined quad effects of massive low-cost computing power, cheap cloud storage, fast internet connectivity and ubiquitous social networks, AI has moved several layers from basic logic automation to machines that can learn for itself without being explicitly programmed to, and to machines can network via cyberspace to reinforce each other to since complex problems with a hint of machine imagination. This rapid evolution of simple AI to “Machine Learning” is the “why” I advocate replacing the human investment manager.

Our SquirrelSave AI does not sleep. It is able to track real-time data and predicts risks and returns 24/7. SquirrelSave AI does not discriminate or ignore you based on how much or how little you invest. We use Nobel Prize-winning Modern Portfolio Theory (MPT) and apply real-time data to find the optimal combination of investment assets that are likely to generate the highest return for the risk you decide to take. We track up to 574,000 real-time investment factors and analyse up to 21 million datasets. We offer you global diversified investing across 5 continents, 15 assets classes and 35 countries covering over 2,000 investment choices. No knowledge needed. Only your risk profile.

It’s time you adopt “Smart Investing” at SquirrelSave!

 — 

Originally posted on SquirrelSave Blog

[spaceexp]

NASA Study Finds Unexpectedly Primitive Atmosphere Around ‘Warm Neptune’

NASA - Hubble Space Telescope patch / NASA - Spitzer Space Telescope patch. May 11, 2017 A study combining observations from NASA’s Hubble and Spitzer space telescopes reveals that the distant planet HAT-P-26b has a primitive atmosphere composed almost entirely of hydrogen and helium. Located about 437 light years away, HAT-P-26b orbits a star roughly twice as old as the sun. The analysis is one of the most detailed studies to date of a “warm Neptune,” or a planet that is Neptune-sized and close to its star. The researchers determined that HAT-P-26b’s atmosphere is relatively clear of clouds and has a strong water signature, although the planet is not a water world. This is the best measurement of water to date on an exoplanet of this size. The discovery of an atmosphere with this composition on this exoplanet has implications for how scientists think about the birth and development of planetary systems. Compared to Neptune and Uranus, the planets in our solar system with about the same mass, HAT-P-26b likely formed either closer to its host star or later in the development of its planetary system, or both. “Astronomers have just begun to investigate the atmospheres of these distant Neptune-mass planets, and almost right away, we found an example that goes against the trend in our solar system,” said Hannah Wakeford, a postdoctoral researcher at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, and lead author of the study published in the May 12, 2017, issue of Science. “This kind of unexpected result is why I really love exploring the atmospheres of alien planets.”

Image above: The atmosphere of the distant “warm Neptune” HAT-P-26b, illustrated here, is unexpectedly primitive, composed primarily of hydrogen and helium. By combining observations from NASA’s Hubble and Spitzer space telescopes, researchers determined that, unlike Neptune and Uranus, the exoplanet has relatively low metallicity, an indication of the how rich the planet is in all elements heavier than hydrogen and helium. Image Credits: NASA/GSFC. To study HAT-P-26b’s atmosphere, the researchers used data from transits— occasions when the planet passed in front of its host star. During a transit, a fraction of the starlight gets filtered through the planet’s atmosphere, which absorbs some wavelengths of light but not others. By looking at how the signatures of the starlight change as a result of this filtering, researchers can work backward to figure out the chemical composition of the atmosphere. In this case, the team pooled data from four transits measured by Hubble and two seen by Spitzer. Together, those observations covered a wide range of wavelengths from yellow light through the near-infrared region. “To have so much information about a warm Neptune is still rare, so analyzing these data sets simultaneously is an achievement in and of itself,” said co-author Tiffany Kataria of NASA's Jet Propulsion Laboratory in Pasadena, California. Because the study provided a precise measurement of water, the researchers were able to use the water signature to estimate HAT-P-26b’s metallicity. Astronomers calculate the metallicity, an indication of how rich the planet is in all elements heavier than hydrogen and helium, because it gives them clues about how a planet formed. To compare planets by their metallicities, scientists use the sun as a point of reference, almost like describing how much caffeine beverages have by comparing them to a cup of coffee. Jupiter has a metallicity about 2 to 5 times that of the sun. For Saturn, it’s about 10 times as much as the sun. These relatively low values mean that the two gas giants are made almost entirely of hydrogen and helium.

Spitzer Space Telescope. Image Credits: NASA/JPL

The ice giants Neptune and Uranus are smaller than the gas giants but richer in the heavier elements, with metallicities of about 100 times that of the sun. So, for the four outer planets in our solar system, the trend is that the metallicities are lower for the bigger planets. Scientists think this happened because, as the solar system was taking shape, Neptune and Uranus formed in a region toward the outskirts of the enormous disk of dust, gas and debris that swirled around the immature sun. Summing up the complicated process of planetary formation in a nutshell: Neptune and Uranus would have been bombarded with a lot of icy debris that was rich in heavier elements. Jupiter and Saturn, which formed in a warmer part of the disk, would have encountered less of the icy debris. Two planets beyond our solar system also fit this trend. One is the Neptune-mass planet HAT-P-11b. The other is WASP-43b, a gas giant twice as massive as Jupiter. But Wakeford and her colleagues found that HAT-P-26b bucks the trend. They determined its metallicity is only about 4.8 times that of the sun, much closer to the value for Jupiter than for Neptune. “This analysis shows that there is a lot more diversity in the atmospheres of these exoplanets than we were expecting, which is providing insight into how planets can form and evolve differently than in our solar system,” said David K. Sing of the University of Exeter and the second author of the paper. “I would say that has been a theme in the studies of exoplanets: Researchers keep finding surprising diversity.”

Hubble Space Telescope. Animation Credits: NASA/ESA

The Hubble Space Telescope is a project of international cooperation between NASA and ESA (European Space Agency). NASA's Goddard Space Flight Center in Greenbelt, Maryland, manages the telescope. The Space Telescope Science Institute (STScI) in Baltimore conducts Hubble science operations. STScI is operated for NASA by the Association of Universities for Research in Astronomy, Inc., in Washington. NASA's Jet Propulsion Laboratory in Pasadena, California, manages the Spitzer Space Telescope for NASA's Science Mission Directorate, Washington. Science operations are conducted at the Spitzer Science Center at Caltech in Pasadena. Spacecraft operations are based at Lockheed Martin Space Systems Company, Littleton, Colorado. Data are archived at the Infrared Science Archive housed at the Infrared Processing and Analysis Center at Caltech. Caltech manages JPL for NASA. For more information about Spitzer, visit: http://www.nasa.gov/spitzer For images and more information about Hubble, visit: http://www.nasa.gov/hubble Images (mentioned), Animation (mentioned), Text, Credits: NASA/Karl Hille/Goddard Space Flight Center/Elizabeth Zubritsky/Nancy Neal-Jones/JPL/Elizabeth Landau. Greetings, Orbiter.ch Full article

[jbaquerot]

Data ethics has exploded into mainstream consciousness in recent weeks, with media coverage of terrorism advertising on YouTube, Cambridge Analytica using Facebook posts to personalise election campaigning, and the endless stream of scandals engulfing taxi-hailing app Uber.

The principles and rules are struggling to keep pace with the technological development. A panel of experts assembled by techUK discussed how to ensure principled behaviour. With ethical notions of consent and privacy constantly stretched by the latest advances in tech, a new structure is needed to establish criteria to protect data.

"You need standards that give you certainty to innovate," says Royal Statistical Society Executive Director Hetan Shah. "Without public trust you could lose your license to operate."

The NHS lost that license in the care.data debacle. Despite widespread support for the concept of using NHS records to improve the health service, the handling of the data protection issue caused an outcry that destroyed the scheme.

Public attitudes to data use Recent scandals around data use have left public trust at a low ebb. The Royal Society recently asked members of the public how much they trust an institution, and how much they would trust that institution with their data.

"The second answer was always lower than the first," says Shah "You'd never trust an institution with your data more than you'd trust it in general. There's a trust deficit, and that's a societal problem."

Claire Craig, the director of science policy at the Royal Society, has been involved in a study asking British citizens of different socio-economic backgrounds their views on the use of data. The qualitiative research revealed that the public's criteria for judging risk begins with perceived motivation.

"The main message is the importance of context," says Craig. "Their basic criteria for judging risk and benefit of a particular application very much start with a perceived motivation.

"They really care why a new technology has been introduced, why a new application, what data, and the purpose. And they care about the beneficiaries. In particular they’re more supportive if they see it helping them, people like them, groups like theirs, and society more generally."

Basically, there need to be direct consumer benefits. Profit was not a problem if the work helped humans.

Any autonomous decision-making driven by data would be assessed based on the perceived level of risk and culpability. Amazon suggestions for example, would be viewed with far less concern than self-driving cars.

They were supportive of applications that enabled more human contact, through results such as freeing up time to spend with friends and family.

The over-reliance on technology could lead to people permanently losing the skills they’ve held for generations.

Technology needs to be proven to augment humanity rather than undermine it. Helping professionals save time for more important work would be widely supported, but automation that could replace them would unsurprisingly make them wary.

"There were big concerns about the being replaced [and] the future of work," says Craig. "Where's the voice for potential new jobs?"

These worries extended to existential fears, as technology sets us on an inevitable pathway towards depersonalisation and challenges the essence of what it means to be human and of value, if a computer than can everything better than they can. If an algorithm had the authority to determine your choices, restrictions on freedom in areas such as career, education and financial support seemed an inevitable consequence.

Building trust

Positive uses of data rarely receive the same exposure as the negative ones. For every Las Vegas casino that uses data science to estimate your spend threshold as you walk in, and when you reach it offer you a drink in order to help you break it, there’s a Streams app improving health outcomes and saving nurses hours each day by scanning patient data to predict acute kidney injury risk.

Trust would be boosted by publicising the positives, such as TfL's use of open data to predict when a bus is coming, or the Food Standards Agency (FSA) monitoring social media for the spread of the Norovirus.

A recent Frontier Economics report predicted that AI could add an additional US$814 billion to the UK’s economy in 2035, and an increase in growth rate 2.5 percent to 3.9 percent.

"The hard numbers are very impressive, but still sell short the way in which these data-driven technologies like data analytics, like artificial intelligence, really can positively transform every aspect of our economy, every aspect of our lives, and really help us build richer, healthier, cleaner communities," says Microsoft UK Government Affairs Manager Owen Larter.

Algorithmic pattern recognition technologies are already being used in the US healthcare system to address preventable errors in hospitals, the third largest cause of deaths after cancer and heart disease. This data-driven pattern recognition can flag anomalies in established clinical best practices to clinicians, and prevent these errors causing significant harm.

The UK today has an ethical imperative to answer the challenges such as the healthcare costs of an ageing population that will mean the NHS of today is no longer affordable tomorrow.

The data troves that we’ve developed can be used save lives, but only if is release can its potential be unleashed, techUK deputy CEO Antony Walker argues.

"I would argue that we have an ethical responsibility to our children and grandchildren if we want them to have a free health service," says Walker. "The only way we can do that is through the use of data."

Attributing accountability can be hard when it comes to code, but making the processes auditable to explain how it works would help build public trust. There also needs to be a response to concerns raised by the public, Craig argues.

"Transparency is necessary but by no means efficient," he says. "Knowing what is happening is only the starting point."

Accountability, responsibility and liability are a complicated triangle. The latter is where it really hurts the company, and where transgressions need to be corrected.

In addition to the aforementioned issues around privacy, governance and consent, public fears persist around data equity and bias. Algorithms are often given more credence than opinions, despite being a product of human sentiments and prejudices.

Data science remains a relatively new discipline so scientists need thorough training in data ethics and standards. The outcomes of the algorithms they design should be audited to ensure transparency and safety.

"It's hard to peer into the black box of algorithms," says Shah.

He wants an independent data ethics council set up, and would rather give existing regulators additional powers than establish new ones.

Into the future

Luciano Floridi, Professor of Philosophy and Ethics of Information at the University of Oxford, has been analysing the potential future of data and the ethical implications that will emerge in the coming years.

He describes two separate outlooks for how AI will develop: "the swimming pool model", which will see the whole world filled to brim with it, and his personal prediction of the "the pothole model", where drips fall on everything, but only fill certain holes up to the top.

"In terms of linking the holes, it won't be AI doing all the work, it'll be humans, it'll be us," he says. "And there will be a lot of ethical issues we'll have to understand about how we work as interfaces between an AI app, and another AI app, and another system that needs to be linked and so on. How you link all this is entirely unchartered territory."

New technology always offers new opportunities for crime, but private companies, public bodies and law enforcement agencies can be slow to catch on. Europol’s 2016 Internet Organised Crime Threat Assessment (IOCTA) has a section for all manner of established cyber crimes, but barely a mention of artificial intelligence.

"There’s a lot of talk about using machine learning, AI to fight organised crime. Is anyone talking about how organised crime is going to use the same technology?” he asks."If you find something in an operating system in some kind that is a vulnerability, can you imagine what that is going to look like once it's a vulnerability that is hackable within an AI system. The only people I know that are talking about this is the car industry."

Algorithms are promoted for their potential to strengthen computer security, but have a similar capacity as a means to overcome it. No longer will they have to hack every individual car's computer, when automation has them all running on the same system.

There are some positive developments inside the private sector, however. Companies increasingly see data ethics as an asset that’s good for business, particularly once they move from a startup to a large enterprise.

Technology can change ethics, such as the contraceptive pill, which provided the protection to trigger a sexual revolution before the public pushed it forward. If data is to begin to fulfil the transformative potential that it offers, ethical rules must be established, and a framework to enforce them. It’s up to the government and the industry to put a new system in place.