#other users have made some really excellent and cutting observations about how she behaves in the e4 outfit
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okay hi i want to talk about agatha's costuming for a sec bc holy fuck do these people know what they're doing. all that follows is my own opinion/analysis.
i could write a whole post about cop!agnes and the butch coding with her but that's not agatha and doesn't count, so we pick up with the robe.
snakes! we love snakes. i think a lot about lilith parallels for agatha. if you look at westview as wanda's constructed eden, and agatha the corruptive force that rips it apart...
more than that, though, this is agatha at the most vulnerable we've ever seen her. she's still on the back foot, sorting through the situation she's in - her neck is bare, her hair is down. rio knows this and is here to capitalise on it. her lack of armour makes the fact that it's possible to touch her, to wound her, all the more apparent
she may hate the style, but this is absolutely not the last we'll see of purple in her 'comfort clothes', so keep that in mind
then we come to the 'witchvengers assemble' outfit. several things here.
first of all, these are agnes' clothes - except the shoes (though from "whose shoes are these?" we gather that they don't belong to her, either. not one single element of this costume does). agatha is, again, putting on the mask of an eccentric suburban sweetheart to get her read on lilia.
she can't bear to do it exactly like agnes again, though, so she adds the throw as a shawl, the pearls from teen's car, the stick in the hair. she wears the blouse loose, where agnes' fashion has historically favoured a tighter silhouette. and from all those things come this new character.
this outfit is very busy - the vertical stripes in the blouse, the geometry in the shawl. agatha is trying to convey mess. she's reaching for humanity. it's so much more approachable than the perfectly put together aesthetic sensibilities adhered to in wanda's westview, where looking like a postcard was the main visual benchmark for whether or not you could be trusted. ever the social chameleon, she recognises the differing demands of this new situation and works with what she's got to meet them.
the power outfit! i love this look so much. i don't think i need to explain to you that this is agatha's attempt at confidence in a situation that leaves her very unmoored - some little fun things of note instead.
that dramatic victorian silhouette with the frock coat. maybe historically-inspired fashion has always been agatha's happy place, or maybe this is another direct reaction to what she's been forced to wear for the past three years. maybe it's both!
agatha likes high collars. she likes to protect her neck, and she likes to be able to move. (see: the supervillainess fit in wv 8 + 9, the 2000s turtleneck, the 80s blouse)
she's keeping her purple close without being gaudy; that lining is gorgeous, and deeply tasteful. following through on that theme of "bringing her into the real world" (daniel selon, lead costumer)
her hair is up - like it often is when she's putting on a front of one kind or another. the hair came down for the reveal in wv too.
her mother's broach is front and centre here. so fascinating to me that she still honours evanora like this even after everything.
well, we spent a couple of hours free from contrived, colour-blocked suburbia...
though she's back in a suburban mom outfit, it's someone else's idea of a suburban mom: jen's. she gets to keep her high collar, but the structured blazer evokes a lack of movement - a sense of being trapped.
the hair and makeup bring in ideals of social media-style perfection, iterating on those expectations in wanda's tv-world. she's able to use the hair to hide behind in a literal sense.
this outfit does a great job of representing why agatha panics so quickly here. it feels like moving backward to her.
all that being the case, this look should be very comfortable by contrast, right? and it is, but there are problems here too.
selon talks about wanting rio and agatha on an "even playing field" here, and that's why they've both got these deep necklines - playing on the coding the robe set up in e1.
agatha has a lot of freedom of movement here, and she (rightly) thinks she looks hot. but this isn't an outfit she would choose for herself. baring her heart is not something she ever does willingly, anymore.
#other users have made some really excellent and cutting observations about how she behaves in the e4 outfit#so i'll leave that to them#but yeah. <3 is anyone going to read this? no idea it was for ME#meta.
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Many voices have claimed that the statisticians lost the election because their predictions were so off the mark. But what if statisticians in fact helped win the election—but only those who were using the new method? It is an irony of history that Trump, who often grumbled about scientific research, used a highly scientific approach in his campaign. Psychometrics, sometimes also called psychographics, focuses on measuring psychological traits, such as personality. In the 1980s, two teams of psychologists developed a model that sought to assess human beings based on five personality traits, known as the “Big Five.” These are: openness (how open you are to new experiences?), conscientiousness (how much of a perfectionist are you?), extroversion (how sociable are you?), agreeableness (how considerate and cooperative you are?) and neuroticism (are you easily upset?). Based on these dimensions—they are also known as OCEAN, an acronym for openness, conscientiousness, extroversion, agreeableness, neuroticism—we can make a relatively accurate assessment of the kind of person in front of us. This includes their needs and fears, and how they are likely to behave. The “Big Five” has become the standard technique of psychometrics. But for a long time, the problem with this approach was data collection, because it involved filling out a complicated, highly personal questionnaire. Then came the Internet. And Facebook. And Kosinski.
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The approach that Kosinski and his colleagues developed over the next few years was actually quite simple. First, they provided test subjects with a questionnaire in the form of an online quiz. From their responses, the psychologists calculated the personal Big Five values of respondents. Kosinski’s team then compared the results with all sorts of other online data from the subjects: what they “liked,” shared or posted on Facebook, or what gender, age, place of residence they specified, for example. This enabled the researchers to connect the dots and make correlations.
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Kosinski and his team tirelessly refined their models. In 2012, Kosinski proved that on the basis of an average of 68 Facebook “likes” by a user, it was possible to predict their skin color (with 95 percent accuracy), their sexual orientation (88 percent accuracy), and their affiliation to the Democratic or Republican party (85 percent). But it didn’t stop there. Intelligence, religious affiliation, as well as alcohol, cigarette and drug use, could all be determined. From the data it was even possible to deduce whether someone’s parents were divorced.
The strength of their modeling was illustrated by how well it could predict a subject’s answers. Kosinski continued to work on the models incessantly: before long, he was able to evaluate a person better than the average work colleague, merely on the basis of ten Facebook “likes.” Seventy “likes” were enough to outdo what a person’s friends knew, 150 what their parents knew, and 300 “likes” what their partner knew. More “likes” could even surpass what a person thought they knew about themselves. On the day that Kosinski published these findings, he received two phone calls. The threat of a lawsuit and a job offer. Both from Facebook.
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But we also reveal something about ourselves even when we’re not online. For example, the motion sensor on our phone reveals how quickly we move and how far we travel (this correlates with emotional instability). Our smartphone, Kosinski concluded, is a vast psychological questionnaire that we are constantly filling out, both consciously and unconsciously.
Above all, however—and this is key—it also works in reverse: not only can psychological profiles be created from your data, but your data can also be used the other way round to search for specific profiles: all anxious fathers, all angry introverts, for example—or maybe even all undecided Democrats? Essentially, what Kosinski had invented was sort of a people search engine. He started to recognize the potential—but also the inherent danger—of his work.
To him, the internet had always seemed like a gift from heaven. What he really wanted was to give something back, to share. Data can be copied, so why shouldn’t everyone benefit from it? It was the spirit of a whole generation, the beginning of a new era that transcended the limitations of the physical world. But what would happen, wondered Kosinski, if someone abused his people search engine to manipulate people? He began to add warnings to most of his scientific work. His approach, he warned, “could pose a threat to an individual’s well-being, freedom, or even life.” But no one seemed to grasp what he meant.
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Finally, Kosinski remembers, Kogan revealed the name of the company: SCL, or Strategic Communication Laboratories. Kosinski Googled the company: “[We are] the premier election management agency,” says the company’s website. SCL provides marketing based on psychological modeling. One of its core focuses: Influencing elections. Influencing elections? Perturbed, Kosinski clicked through the pages. What kind of company was this? And what were these people planning?
What Kosinski did not know at the time: SCL is the parent of a group of companies. Who exactly owns SCL and its diverse branches is unclear, thanks to a convoluted corporate structure, the type seen in the UK Companies House, the Panama Papers, and the Delaware company registry. Some of the SCL offshoots have been involved in elections from Ukraine to Nigeria, helped the Nepalese monarch against the rebels, whereas others have developed methods to influence Eastern European and Afghan citizens for NATO. And, in 2013, SCL spun off a new company to participate in US elections: Cambridge Analytica.
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Kosinski came to suspect that Kogan’s company might have reproduced the Facebook “Likes”-based Big Five measurement tool in order to sell it to this election-influencing firm. He immediately broke off contact with Kogan and informed the director of the institute, sparking a complicated conflict within the university. The institute was worried about its reputation. Aleksandr Kogan then moved to Singapore, married, and changed his name to Dr. Spectre. Michal Kosinski finished his PhD, got a job offer from Stanford and moved to the US.
All was quiet for about a year. Then, in November 2015, the more radical of the two Brexit campaigns, “Leave.EU,” supported by Nigel Farage, announced that it had commissioned a Big Data company to support its online campaign: Cambridge Analytica. The company’s core strength: innovative political marketing—microtargeting—by measuring people’s personality from their digital footprints, based on the OCEAN model.
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After the Brexit result, friends and acquaintances wrote to him: Just look at what you’ve done. Everywhere he went, Kosinski had to explain that he had nothing to do with this company. (It remains unclear how deeply Cambridge Analytica was involved in the Brexit campaign. Cambridge Analytica would not discuss such questions.)
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A few weeks earlier, Trump had tweeted, somewhat cryptically, “Soon you’ll be calling me Mr. Brexit.” Political observers had indeed noticed some striking similarities between Trump’s agenda and that of the right-wing Brexit movement. But few had noticed the connection with Trump’s recent hiring of a marketing company named Cambridge Analytica.
Up to this point, Trump’s digital campaign had consisted of more or less one person: Brad Parscale, a marketing entrepreneur and failed start-up founder who created a rudimentary website for Trump for $1,500. The 70-year-old Trump is not digitally savvy—there isn’t even a computer on his office desk. Trump doesn’t do emails, his personal assistant once revealed. She herself talked him into having a smartphone, from which he now tweets incessantly.
Hillary Clinton, on the other hand, relied heavily on the legacy of the first “social-media president,” Barack Obama. She had the address lists of the Democratic Party, worked with cutting-edge big data analysts from BlueLabsand received support from Google and DreamWorks. When it was announced in June 2016 that Trump had hired Cambridge Analytica, the establishment in Washington just turned up their noses. Foreign dudes in tailor-made suits who don’t understand the country and its people? Seriously?
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“So how did he do this?” Up to now, explains Nix, election campaigns have been organized based on demographic concepts. “A really ridiculous idea. The idea that all women should receive the same message because of their gender—or all African Americans because of their race.” What Nix meant is that while other campaigners so far have relied on demographics, Cambridge Analytica was using psychometrics.
Though this might be true, Cambridge Analytica’s role within Cruz’s campaign isn’t undisputed. In December 2015 the Cruz team credited their rising success to psychological use of data and analytics. In Advertising Age, a political client said the embedded Cambridge staff was “like an extra wheel,” but found their core product, Cambridge’s voter data modeling, still “excellent.” The campaign would pay the company at least $5.8 million to help identify voters in the Iowa caucuses, which Cruz won, before dropping out of the race in May.
Nix clicks to the next slide: five different faces, each face corresponding to a personality profile. It is the Big Five or OCEAN Model. “At Cambridge,” he said, “we were able to form a model to predict the personality of every single adult in the United States of America.” The hall is captivated. According to Nix, the success of Cambridge Analytica’s marketing is based on a combination of three elements: behavioral science using the OCEAN Model, Big Data analysis, and ad targeting. Ad targeting is personalized advertising, aligned as accurately as possible to the personality of an individual consumer.
Nix candidly explains how his company does this. First, Cambridge Analytica buys personal data from a range of different sources, like land registries, automotive data, shopping data, bonus cards, club memberships, what magazines you read, what churches you attend. Nix displays the logos of globally active data brokers like Acxiom and Experian—in the US, almost all personal data is for sale. For example, if you want to know where Jewish women live, you can simply buy this information, phone numbers included. Now Cambridge Analytica aggregates this data with the electoral rolls of the Republican party and online data and calculates a Big Five personality profile. Digital footprints suddenly become real people with fears, needs, interests, and residential addresses.
The methodology looks quite similar to the one that Michal Kosinski once developed. Cambridge Analytica also uses, Nix told us, “surveys on social media” and Facebook data. And the company does exactly what Kosinski warned of: “We have profiled the personality of every adult in the United States of America—220 million people,” Nix boasts.
He opens the screenshot. “This is a data dashboard that we prepared for the Cruz campaign.” A digital control center appears. On the left are diagrams; on the right, a map of Iowa, where Cruz won a surprisingly large number of votes in the primary. And on the map, there are hundreds of thousands of small red and blue dots. Nix narrows down the criteria: “Republicans"—the blue dots disappear; "not yet convinced"—more dots disappear; "male”, and so on. Finally, only one name remains, including age, address, interests, personality and political inclination. How does Cambridge Analytica now target this person with an appropriate political message?
Nix shows how psychographically categorized voters can be differently addressed, based on the example of gun rights, the 2nd Amendment: “For a highly neurotic and conscientious audience the threat of a burglary—and the insurance policy of a gun.” An image on the left shows the hand of an intruder smashing a window. The right side shows a man and a child standing in a field at sunset, both holding guns, clearly shooting ducks: “Conversely, for a closed and agreeable audience. People who care about tradition, and habits, and family.”
Trump’s striking inconsistencies, his much-criticized fickleness, and the resulting array of contradictory messages, suddenly turned out to be his great asset: a different message for every voter. The notion that Trump acted like a perfectly opportunistic algorithm following audience reactions is something the mathematician Cathy O'Neil observed in August 2016.
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The messages differed for the most part only in microscopic details, in order to target the recipients in the optimal psychological way: different headings, colors, captions, with a photo or video. This fine-tuning reaches all the way down to the smallest groups, Nix explained in an interview with us. “We can address villages or apartment blocks in a targeted way. Even individuals.”
In the Miami district of Little Haiti, for instance, Trump’s campaign provided inhabitants with news about the failure of the Clinton Foundation following the earthquake in Haiti, in order to keep them from voting for Hillary Clinton. This was one of the goals: to keep potential Clinton voters (which include wavering left-wingers, African-Americans, and young women) away from the ballot box, to “suppress” their vote, as one senior campaign official told Bloomberg in the weeks before the election. These “dark posts"—sponsored news-feed-style ads in Facebook timelines that can only be seen by users with specific profiles—included videos aimed at African-Americans in which Hillary Clinton refers to black men as predators, for example.
Nix finishes his lecture at the Concordia Summit by stating that traditional blanket advertising is dead. "My children will certainly never, ever understand this concept of mass communication.” And before leaving the stage, he announced that since Cruz had left the race, the company was helping one of the remaining presidential candidates.
Just how precisely the American population was being targeted by Trump’s digital troops at that moment was not visible, because they attacked less on mainstream TV and more with personalized messages on social media or digital TV. And while the Clinton team thought it was in the lead, based on demographic projections, Bloomberg journalist Sasha Issenberg was surprised to note on a visit to San Antonio—where Trump’s digital campaign was based—that a “second headquarters” was being created … Whereas European privacy laws require a person to “opt in” to a release of data, those in the US permit data to be released unless a user “opts out.”
The measures were radical: From July 2016, Trump’s canvassers were provided with an app with which they could identify the political views and personality types of the inhabitants of a house. It was the same app provider used by Brexit campaigners. Trump’s people only rang at the doors of houses that the app rated as receptive to his messages. The canvassers came prepared with guidelines for conversations tailored to the personality type of the resident. In turn, the canvassers fed the reactions into the app, and the new data flowed back to the dashboards of the Trump campaign.
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But to what extent did psychometric methods influence the outcome of the election? When asked, Cambridge Analytica was unwilling to provide any proof of the effectiveness of its campaign. And it is quite possible that the question is impossible to answer.
And yet there are clues: There is the fact of the surprising rise of Ted Cruz during the primaries. Also there was an increased number of voters in rural areas. There was the decline in the number of African-American early votes. The fact that Trump spent so little money may also be explained by the effectiveness of personality-based advertising. As does the fact that he invested far more in digital than TV campaigning compared to Hillary Clinton. Facebook proved to be the ultimate weapon and the best election campaigner, as Nix explained, and as comments by several core Trump campaigners demonstrate.
Many voices have claimed that the statisticians lost the election because their predictions were so off the mark. But what if statisticians in fact helped win the election—but only those who were using the new method? It is an irony of history that Trump, who often grumbled about scientific research, used a highly scientific approach in his campaign.
Another big winner is Cambridge Analytica. Its board member Steve Bannon, former executive chair of the right-wing online newspaper Breitbart News, has been appointed as Donald Trump’s senior counselor and chief strategist. Whilst Cambridge Analytica is not willing to comment on alleged ongoing talks with UK Prime Minister Theresa May, Alexander Nix claims that he is building up his client base worldwide, and that he has received inquiries from Switzerland, Germany, and Australia. His company is currently touring European conferences showcasing their success in the United States. This year three core countries of the EU are facing elections with resurgent populist parties: France, Holland and Germany. The electoral successes come at an opportune time, as the company is readying for a push into commercial advertising.
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The world has been turned upside down. Great Britain is leaving the EU, Donald Trump is president of the United States of America. And in Stanford, Kosinski, who wanted to warn against the danger of using psychological targeting in a political setting, is once again receiving accusatory emails. “No,” says Kosinski, quietly and shaking his head. “This is not my fault. I did not build the bomb. I only showed that it exists."
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