#incorrect rote

[sterlingterror]

I think Fitz is incredibly oblivious to the fact that at least half of the resons why everyone thought Lord Golden was railing him are squarely on him.

He spends half of his time just staring admiringly at his bestest friend with moony eyes waxing poetically in his head about how pretty and regal and perfect and fashionable he is. How charismatic and personable. How very golden. My guy.

Not just that, he relentlessly fucked up the whole pretending to be a servant thing, so of course everyone said 'oh yeah, definitely secret lovers or else he would be so incredibly fired'. So much for being a trained spy.

[fitzbelovedhangover]

Imagine a scene in the future potential Bee book, with Bee, 12, at school:

Teacher: children, children... so today we are gonna talk about prophets and catalysts... In our History, there were plenty of them, some were close friends, some hated each other, some didnt care...But one pair particularly stayed in our hearts as true legends, gone a few years ago, way too soon...-winks at Bee- The pair of the Bastard Prince and the Golden Jester...

Bee: oh boy, not again...💀💀💀

[barbatosgossipsection]

I'm not AGAINST incorrect quotes as a form of shitpost. They're low effort high reward by nature but man some of you aren't even trying!!! You're just slapping their names into a generator and copy pasting whatever lolfunny conversation from a sitcom it gives you??? You could at least consider which characters would actually say what and which way round would be funniest

Or... hear me out... you could make your own jokes. Some of these quotes are so rote and circulated by now that they're not even funny anymore, they're just tired. Let them retire. Make something from your heart

— Anon

[the-perfect-wagnerite-again]

Hello! Why didn’t you like guns germs and steel? I was thinking of reading it but I just wanted a heads up. Thank you a lot!

So it's not that it's a bad book exactly, but it's certainly not great. A good comparison would be the narrative of the American Revolution that you learned about in elementary and middle school. The particular facts, dates, and rote recitation of individual events is probably mostly correct, but the narrative structure that enframes and coheres those isolated nodes of information is entirely without historical merit.

In Diamond's case, the narrative that he chooses to use to interpret all facts and events that he considers relevant to the story of human development is geographical distribution, to the explicit exclusion of any other vector of influence. To this end, Diamond onboards plainly incorrect assumptions about the human species (such as the assumption that all human beings are neurologically identical) and begs the question on the material causes of nonmaterial developments (religious practice is an outgrowth of material circumstances, the reverse is never mentioned).

A particular peeve I have with Diamond is his out-of-hand dismissal of IQ as a legitimate measure of intelligence. In his introduction, he glibly slides past IQ tests as unimportant trivia quizzes, as if the reason the natives of New Guinea perform poorly is because such tests are asking subjects to identify Bach fugue subjects or determine mathematical operation orders. Diamond is well aware, as is anyone who has ever taken an IQ test, that such exams measure abstract cognitive power through such problems as pattern-recognition and spatial reasoning, problems utterly divorced from cultural influence or environmental factors. There is, to date, no measure of cognitive aptitude as accurate and correlative with intelligence as IQ - which is precisely why we use it. Those who assume a priori that all human beings innately have identical neurological profiles are obligated to ignore this fact, because the reality of performance disparities between groups is politically inconvenient for their emotionally-informed assumption. It is with this dismissal of reality that Diamond can assert such absurdities as "New Guinea natives might actually be smarter than most modern Europeans" (this is based, as far as I can tell, exclusively on Diamonds personal experience with the local tribesmen of Papua New Guinea during his excursions there).

With that in mind, every relevant fact that Diamond selects as a necessary step in the development of human societies is "true" in the sense that, in a vacuum, there is mostly likely a positive truth-value to the individual assertions he presents. Most inventions are accidental. Most technologies are spread through cultural exchange. Most agricultural developments depend on beasts of burden. All of this is true. In aggregate, Diamond takes these facts as excuses to explain away the poor development of sub-Saharan Africans and reframe the advancements of Europeans as the products of chance, accident, and luck.

I would say that the biggest flaw of the book is Diamond's position that geographical distribution is the ONLY factor in human development, rather than one factor of many. The spiritual drive of a people, its native psychometric capacity, and its coevolutionary characteristics are every bit as important as its access to material resources, if not more important ( e.g. as regulatory vectors for those resources in the first instance). Read it with a heaping pile of salt.

[mira-rachel]

MASTERLIST

Fandoms:

Undertale, Hetalia, Countryhumans, Creepypasta, BNHA/MHA, Harry Potter, Ouran High School Host Club, Alice Academy

Reqs

Soulswap DT verse

-

Sketches: [ 1 ]

Dream: [ 2 ]

Incorrect Quotes: [ 1 ], [ 2 ], [ 3 ], [ 4 ], [ 5 ], [ 6 ]

Scenarios: [ 1 ]

Undertale Dungeon AU

Headcannons: [ 1 ],

Rise Of The Empires CH AU [rote au]

Headcannons [ 1 ], [ 2 ], [ 3 ]

Dynasty AU

Character's [ 1 ]

Hetalia

Benimaru Kirkland HC [ 1 ], [ 2 ]

Arts

Roundmare [UT/DT]

Strawberry? [UT]

Shark Eduard/Hetalia OC [Hetalia]

Gangsta Eduard [Hetalia]

Idk, pic of Reaper? [UT]

Random Writings

Rants [ 1 ],

Humans are parasites? [Theory]

[majesticbullshit]

When I was in second grade, my neurodivergence was having a bigger impact on my schooling experience. I'm told that my first grade teacher let me slide a bit, but that that time was over and now I needed to make improvements. I found it difficult to engage with any of the material. My mom had to have more and more meetings with my teacher, discussions of me being retained were thrown around.

I lay a large amount of credit for my improvement in that era at the feet of Dragon Ball. My older brother was an avid comic fan, and on a trip to the comics shop I saw the then comic book formatted issues of Dragon Ball. The cover art immediately drew me in, and for the first time I was reading on my own initiative. I didn't understand to read them right to left yet, so you can bet your ass I was confused at first, but I read them incorrect cover to incorrect cover enough times to recite them by rote.

That was my introduction to the idea that reading could actually be something that one can enjoy, not just something one has to do because a teacher is telling them to. Dragon Ball comics became the incentive my mother would buy me if I brought my grades up. I was watching fucked up fan subs of the anime one single frame at a time on my grandma's shit ass Internet, but reading captions all the same.

Reading Dragon Ball lead to reading Spider-Man comics, which lead to reading (and re-reading ad nauseam, have I mentioned the neurodivergence?) The Eyewitness Story of Spider-Man by Michael Teitelbaum, which lead to reading every single Eye Witness animal book, which lead to novels, which lead me to where I am today, my living room littered with bookshelves (and piles of unread books that I'm going to get to, of course)

I think of the butterfly effect Dragon Ball had on me and it almost scares me how much that one comic with the sick cover set my life in motion. If I never found an earnest love of reading, how much harder would college have been, would I have my current career in education, etc etc.

I am where I am today at least partially due to the work of Akira Toriyama. It felt only right to eulogize him. Thank you, and rest in peace.

[landwriter]

I have a question that has absolutely nothing to do with fic or the Sandman except for the bit where it's about a dream poem! Since you've minored in French literature, I was wondering if you've read Le Roman de la Rose? As far as medieval dream poems go, Chaucer and even Lydgate can take a back seat because the first part of Le Roman (aka the part written by Guillaume de Lorris c. 1230) is fantastic and contains some of my favourite language ever. The God of Love makes the Lover kiss his mouth which drives me crazy, but these lines are my favourite in any literature ever and honestly this entire ask is me just jumping on the chance to share them/write them out again (the English translation is by Charles Dahlberg):

lors la me toucha au costé et ferma mon cuer si souef qu'a grant poine senti la clef

then he touched my side and locked my heart so softly that I hardly felt the key

I have not - furthest back I was ever sent was late 17th c.

However, after recovering from being absolutely fucking bodied by those lines, I wanna read it. I've done a semi-cursory search and have only found it in English translations, and a French journal article about how many manuscripts there's been of Le Roman de la Rose (answer: a great deal) but I would love even the Guillaume de Lorris portion? I am hooked. thank you for this. a small digression *I* am jumping on the chance to talk abt:

This is a good example of a funky little modern French thing, which is pronouncing the vestigial -e (there's actual terms but I like vestigial) that would otherwise be silent (for the most part, regionally, asterisk asterisk etc.,) in speech, in prose - but are pronounced in poetry and song. Francophones are like 'it's for meter' (as above in poine, to make the line 8 syllables) but as usual they are being incredibly blasé about a very cool linguistic convention. Why is it cool? It's a remnant of both our language's histories! It used to be our convention too!

As anyone who has read Middle English in Dreamling fic, completely new to it, as I was, you will notice the profusion of seemingly vestigial -e's. While spelling was not standardized, there's overall more of them on words today we might recognize which have since shed them completely, like the classic myne owne hertis rote (x), my own heart's root. If you're an Anglo like me, you might read that and pronounce it something like 'mine own heart-iss wrote'. BUT! Guess the fuck what - just like in French poetry even today, these final e's were pronounced for the majority of what we call 'Middle English'. Here is someone reading some of Chaucer's Canterbury Tales in Middle English. It's so jaunty, eh?

Unlike the French, we have obviously not kept the habit of pronouncing our now-vestigial -e's, even in spoken verse. (or, if u will, vers-uh) I think it's a crying shame. The music of it! The rhythm! The connection with your linguistic ancestors! My tinfoil hat thesis that is objectively incorrect but feels right: we doomed this gorgeous facet of English pronunciation in the rise of literacy and printing; if we still primarily transmitted stories via oral tradition they would sound prettier. The French kept it because they relied on it too much in their poetry are simply more stubborn and consistent.

On that theme, I think it's crazy how much more comprehensible Old French is relative to modern French, than even Middle English a few centuries later vs modern English?? What's up with that?

p.s. any asks that are like 'here's some ruinous language I would like to share with you' are very welcome they don't even have to be dream poems!

p.p.s. more on Middle English pronunciation from someone that might know what they're talking about because I certainly do not (x)

[rinshiroufan]

I've come to the conclusion recently that eloquent and sophisticated essays providing apologia for Rin/Shirou are pointless. It scarcely matters how compelling and articulate the argumentation is, or how well the passages adduced bolster the central thrust of the lucubration, if someone simply didn't initially understand Rin, they never will. Not really. I have lost track of how many times I have managed to "sway" someone around to appreciating Rin and the UBW romance more, with their proving themselves to be perfunctorily adroit at regurgitating my own prolix ramblings, and even rhetorically gifted at insufflating their own essays with impressive rhetorical flourish and ornate, evocative imagery, only for them to subsequently demonstrate themselves as congenitally incapable of truly applying what they had learned (through rote memorization) to reach deeper insights about the character on their own. If I didn't hold their hand like a fucking baby and condescended to them, they would never realize their errors.

Rin/Shirou is something that you simply intuitively understand, or you don't. You can certainly produce analyses, but you should never do so with the expectation that that is going to truly convince anyone. I certainly don't think the romance was a particularly abstruse and opaque part of the story, but for some reason it does appear that one needs access to mystical arcane means to comprehend it. But really, what's the point of deservedly singing the praises of Your distortion if you're going to spew bullshit like Rin was adapted well in the HF films (remember, it doesn't matter how much you explain to someone the nuances of Rin's character in HF and how her relationship with Shirou is crucial to groking her out, they'll still see her as nothing more than a support pillow for Sakura (the sisters storyline really was a mistake), and Rin is nothing but that in the HF films, so it works out for them right) or just spew factually incorrect, easily disprovable nonsense like "Shirou doesn't stay with Rin or settle down to have a family with her in UBW" (could the UBW ending poem and anime finale be more explicit, you morons?)...?

And this admittedly enough doesn't apply simply to Rin. I am perfectly willing to admit that I myself have many blindspots and there are many characters that I appreciate on a technical level but cannot confidently say I meaningfully comprehend (not just in FSN, but in general). The difference would ultimately be however that I simply don't discuss those subjects and characters. But some feel compelled to pontificate at length about Rin and spread contumely against her, whether intentionally or unintentionally. Just please shut the fuck up and don't discuss her at all if you're too obtuse to get it.

Anyway, I intend to write something on the underappreciated aspects of Rin and Archer's character dynamic, and its role in UBW. Been planning it for months, but things kept coming up.

[burr-ell]

thesis: incorrect quotes are only funny when they're adding something to both source materials. data: the "snake juice is basically rat poison" scene from parks and rec can either be rote and predictable or absolutely hilarious depending entirely on who you cast as ron

[nimblermortal]

And this one, stolen from Pinterest, is peak CFSD aesthetic, bordering on the mental image in my head, though the print there is slightly different. (A little less busy, smaller/simpler flowers, slightly different shade of blue.)

The thing about CFSD is that it is inherently an Incorrect aesthetic opinion. That's... one reason I hate shopping is that I have an underlying understanding that there are Aesthetics, and there are Correct and Incorrect opinions, and that I don't know the rules and can't possibly learn them except by rote except that nobody says what the rules are and so I will always, always be Incorrect and every single choice I make is wrong and judged.

...it's a very autistic idea to have.

Anyway CFSD is very much Incorrect. It's Plain and Dowdy and Bad. But I do like it, in my hopelessly Incorrect way.

[swampgallows]

this happened in 2020 with the CDC and epidemiologists insisting that covid spreads through water droplets and not aerosols: they were relying on the rote memorization of data that was over half a century old, and it wasn't until an intern double-checked the cdc's sources that experts were forced to reconsider that covid was actually airborne.

They [the CDC] plucked the size of the particle that transmits tuberculosis out of context, making 5 microns stand in for a general definition of airborne spread. Wells’ 100-micron threshold got left behind. “You can see that the idea of what is respirable, what stays airborne, and what is infectious are all being flattened into this 5-micron phenomenon,” Randall says. Over time, through blind repetition, the error sank deeper into the medical canon. 

tens of thousands of people died in the months of experts prioritizing handwashing and disinfecting surfaces and maintaining a 6 foot distance from others as the best method of prevention, denying that covid can both circulate and remain in the air for potentially hours without ventilation or filtration, all because they were quoting an incorrect figure implicitly accepted as fact. after pressure from the scientists in the article they quietly updated their precautions, but to this day their stance is still one that downplays the precautions necessary against airborne transmission, like filtration (masking, hepa, etc.) and ventilation.

hbomberguy’s latest video on plagiarism has made me completely rethink literature and writing. I have never once so much as considered intentionally plagiarizing anyone or anything, but I there’s something more that has come out of this and it’s the names of the people who created the works Somerton (and others) ripped off.

Plagiarism isn’t just bad because it is lazy and disrespectful, it’s bad because it buries the truth. If you can’t find a source, the conversation is over. Somerton’s sources are fairly easy to find by simply searching his plagiarized lines, but that isn’t true in most cases. Most of the time, the line is a lot less clear.

Today, I was writing a report on English Ivy, which is an invasive species here in the US. I wanted to know when it was introduced and I at last found a source claiming it was introduced to the US “as early as 1727” on a .net website that seems quite reputable (it has multiple major universities credited in its home page), but there is no citation for where this date came from. I dug deeper and found a pamphlet created by a city government in Virginia that made the same claim, only to discover the first source linked in their bibliography. Another website (a botanical garden’s page) gave the same date with the same source hyperlinked. Of course, I have classes to attend and things to do and probably not enough time to follow the lines back to where this 1727 date came from, but if I had not just watched this video, I wouldn’t have given that date a second thought.

Of course, it doesn’t matter in the long run exactly what year hedera helix was introduced to the US, but it makes you wonder how many facts have been so vaguely attributed that it becomes completely impossible to figure out where they originated (and further, whether or not they’re true at all).

[educationtech]

Top 5 Ways to Score well in Class 12th CBSE Chemistry — Arya College

It is the best subject which is taught by Arya College of Engineering & I.T. which is the best engineering college in Jaipur. A solid understanding of key reactions and equations is crucial for excelling in Class 12 Chemistry. This guide will cover essential reactions, strategies for mastering them, and tips for effective study.

Key Reactions and Equations

1. Balancing Chemical Equations

Balancing equations is fundamental in chemistry as it ensures the law of conservation of mass is upheld. Here are some examples:

•           Lithium and Nitrogen:

6Li(s)+N2(g)→2Li3N(s)6Li(s)+N2(g)→2Li3N(s)

This reaction demonstrates a combination reaction where lithium nitride is formed.

•           Sodium and Chlorine:

2Na(s)+Cl2(g)→2NaCl(s)2Na(s)+Cl2(g)→2NaCl(s)

•           Rubidium and Sulfur:

2Rb(s)+S(s)→Rb2S(s)2Rb(s)+S(s)→Rb2S(s)

•           Cesium and Water:

2Cs(s)+2H2O(l)→2CsOH(aq)+H2(g)2Cs(s)+2H2O(l)→2CsOH(aq)+H2(g)

2. Types of Reactions

Understanding different types of chemical reactions can help in predicting products:

•           Combination Reactions: Two or more substances combine to form a product.

•           Decomposition Reactions: A single compound breaks down into two or more products.

•           Displacement Reactions: An element displaces another in a compound.

3. Stoichiometry

Mastering stoichiometry allows you to calculate reactants and products in chemical reactions. For example, the coefficients represent the molar ratios needed for calculations in the reaction between cesium and water.

Study Strategies

Conceptual Understanding

•           Focus on understanding the underlying concepts rather than rote memorization. For instance, grasp why certain elements react with specific compounds based on their positions in the periodic table.

Practice Problems

•           Regularly solve practice problems to reinforce your understanding. Use NCERT solutions and other revision notes to find a variety of exercises.

Visual Aids

•           Create charts or flashcards summarizing key reactions, their products, and conditions. Visual aids can help in memorizing complex information.

Group Study

•           Engage in group studies to discuss difficult concepts. Teaching peers can reinforce your understanding.

Regular Revision

•           Set aside time for regular revision of previous chapters to maintain a strong grasp of fundamental concepts that are often built upon later.

Utilize Resources

•           Use textbooks, online resources, and educational videos to supplement your learning. Websites like Extramarks provide comprehensive notes on chemical kinetics and other topics relevant to Class 12 Chemistry.

What are the most common mistakes students make when balancing chemical equations

When balancing chemical equations, students often encounter several common mistakes that can hinder their understanding and accuracy. Here are the most frequent errors made during this process:

1. Misunderstanding Chemical Formulas

Many students struggle with the basic concept of chemical formulas. A lack of understanding can lead to incorrect representations of compounds, which in turn affects the balancing process. For instance, students may confuse the composition of ionic and covalent compounds or misinterpret the significance of subscripts and coefficients in formulas.

2. Confusing Coefficients and Subscripts

A prevalent mistake is altering subscripts instead of adding coefficients to balance an equation. Subscripts indicate the number of atoms in a molecule and should not be changed, as doing so alters the identity of the substance. Coefficients, on the other hand, indicate how many molecules or moles of a substance are involved in the reaction and can be adjusted to achieve balance.

3. Neglecting to Balance All Elements

Students often focus on balancing prominent elements like carbon and hydrogen while overlooking others such as oxygen or nitrogen. This oversight can lead to an incomplete or incorrect balance of the equation. It is essential to ensure that all elements are accounted for and balanced properly.

4. Incorrect Use of Brackets with Polyatomic Ions

When dealing with polyatomic ions, students frequently misuse brackets, leading to incorrect formulas. Understanding how to properly represent these ions is crucial for accurate balancing.

5. Forgetting Oxygen Balancing

In combustion reactions, students may neglect to balance oxygen atoms correctly, often leaving them until last. Since oxygen is typically a diatomic molecule (O₂), this can complicate balancing if not approached systematically from the beginning

6. Not Checking Final Equations

After balancing an equation, students sometimes fail to double-check their work. It is vital to verify that the number of atoms for each element is equal on both sides of the equation and that coefficients are in their simplest whole-number ratios

7. Ignoring Charge Balance in Redox Reactions

In redox reactions specifically, students may forget to balance charges along with atoms. Ensuring that both mass and charge are conserved is critical for accurately representing these types of reactions

Conclusion

Scoring well in Class 12 Chemistry requires a blend of understanding key reactions, practicing regularly, and employing effective study strategies. Focus on balancing equations, recognizing reaction types, and applying stoichiometry to ensure success in your examinations. Regular revision and practice will solidify your knowledge and prepare you for any challenges that may arise in your chemistry studies.

[samsoncourses]

Comprehensive PLAB Part 1 Revision Guide for Success

Introduction

The Professional and Linguistic Assessments Board (PLAB) exam, administered by the General Medical Council (GMC) in the UK, is essential for international medical graduates aiming to practice in the UK. This two-part examination assesses the candidate’s knowledge, clinical skills, and English proficiency, aligning their competency with a UK-trained doctor’s first year of the Foundation Program (FY1). The PLAB Part 1 exam is the first step, focusing on theoretical medical knowledge across various specialties. Preparing thoroughly is crucial, as Part 1 requires a solid understanding of medical principles and problem-solving skills.

This guide will help you strategize for the PLAB Part 1 revision exam, covering revision techniques, resources, and a study plan to help you succeed. Additionally, we’ll address five frequently asked questions about the exam, making this an all-in-one guide for your PLAB Part 1 journey.

Overview of PLAB Part 1 Exam

Exam Format

The PLAB Part 1 exam consists of 180 multiple-choice questions to be completed in three hours. Each question presents a clinical scenario, followed by a single-best-answer (SBA) option. The focus is on testing practical knowledge and the application of medical concepts, as you would in real-life patient scenarios.

Key Topics Covered

The exam content covers:

Medicine

Surgery

Pediatrics

Psychiatry

Obstetrics and Gynecology

Ethics and legal issues in medicine

Understanding how these areas overlap and are applied in a clinical setting is essential. Focus on honing your analytical skills and applying knowledge to realistic clinical situations rather than rote memorization.

Effective PLAB Part 1 Revision Strategies

Develop a Study Plan

Set a Realistic Schedule: Create a timetable that allows for comprehensive revision of each topic area. Allocate more time to subjects you find challenging and incorporate breaks to avoid burnout.

Prioritize High-Yield Topics: Medicine, surgery, and pediatrics tend to have higher weightage. Make these areas a priority, focusing on clinical guidelines, common presentations, and management strategies.

Use Reliable Study Resources

Official GMC Blueprint: Familiarize yourself with the PLAB Part 1 blueprint provided by the GMC. This document outlines key topics, skills, and knowledge expected for the exam.

Question Banks: Online question banks, such as PLABable, Pastest, and Passmedicine, are tailored for PLAB exams. These resources allow you to practice multiple-choice questions and reinforce your understanding.

Textbooks and Guidelines: Essential medical textbooks, such as Oxford Handbooks, and NICE guidelines are excellent resources for covering fundamental and UK-specific medical practices.

Practice Time Management

Simulate Exam Conditions: During practice sessions, try to complete sets of 180 questions in three hours. This will help you gauge your pace and improve time management skills, essential for finishing the exam comfortably.

Identify Weak Areas Early: As you practice, keep track of topics where you’re consistently scoring lower. Allocate more time to review and strengthen these areas.

Understand the Question Types

Focus on Clinical Scenarios: The PLAB Part 1 exam emphasizes real-life medical situations. Go beyond textbook definitions and understand the clinical presentation, diagnosis, and management.

Single-Best Answer (SBA) Strategy: For SBA questions, identify keywords in the question stem. Practice eliminating incorrect options systematically to improve accuracy.

Join Study Groups or Online Forums

Collaborate with Peers: Join online forums or social media groups, like those on Facebook or Reddit, where PLAB aspirants discuss questions, share resources, and clarify doubts.

Interactive Discussions: Exchanging knowledge with others can expose you to different perspectives and help solidify your understanding of complex topics.

Recommended PLAB Part 1 Revision Resources

PLABable: This platform offers extensive question banks specifically for PLAB. With explanations for each question and a focus on high-yield topics, it’s ideal for targeted revision.

Passmedicine: Known for its well-curated questions and topic explanations, Passmedicine is useful for reinforcing core concepts and testing practical application.

NICE Guidelines: Since UK practice heavily relies on NICE guidelines, reviewing these will help you understand the standard protocols and patient management strategies expected on the exam.

Oxford Handbook of Clinical Medicine: This resource covers concise clinical guidelines, essential for mastering theoretical and practical knowledge in medicine.

Pastest: Another question bank with an extensive range of practice questions and mock exams. Pastest’s analytics also help track progress and weak areas effectively.

Sample Study Plan for PLAB Part 1 (8-Week Program)

Week 1-2: Foundation Topics

Focus: Medicine and Surgery

Review topics like cardiology, gastroenterology, respiratory medicine, and emergency surgery. Practice questions after each chapter to reinforce learning.

Week 3-4: Core Clinical Topics

Focus: Pediatrics and Obstetrics/Gynecology

Study neonatal care, child development milestones, antenatal care, and gynecological conditions. Use guidelines and case-based questions.

Week 5-6: Psychiatry and Other Specialties

Focus: Psychiatry, Ethics, and Law

Review mental health management, ethics, and medico-legal scenarios. Practice questions in ethics and law to understand UK-specific healthcare expectations.

Week 7: Revision and Mock Exams

Take full-length mock exams under timed conditions to evaluate your readiness. Revisit any weak areas identified during these exams.

Week 8: Final Review and Relaxation

Reassess high-yield topics and perform a final, comprehensive revision. Focus on maintaining a calm mindset and avoid cramming new information at this stage.

Top FAQs About PLAB Part 1

How much time is recommended for PLAB Part 1 preparation?

While the time required varies by individual, most candidates find that 2-3 months of focused study is adequate. This should involve around 4-5 hours of study per day, especially if working through comprehensive resources like question banks and textbooks.

Can I take PLAB Part 1 outside the UK?

Yes, the PLAB Part 1 exam is available in various countries worldwide, including India, Egypt, and Pakistan, among others. You can find the list of test centers on the GMC website and select one that’s convenient for you.

What is the passing score for PLAB Part 1?

The passing score is variable and is set by the GMC for each exam sitting based on the overall performance of candidates. Generally, the cut-off ranges between 120-130 out of 180 questions.

What is the most effective way to practice for the exam?

Using question banks that mimic the PLAB Part 1 format is highly effective. Review explanations for each answer thoroughly and focus on improving your accuracy and speed. Mock exams are also invaluable for understanding the pace needed to complete all questions within the time limit.

What happens after passing PLAB Part 1?

After passing Part 1, candidates can apply to sit for PLAB Part 2, which assesses clinical skills through practical scenarios. You will need to travel to the UK to take PLAB Part 2, as it is only available at the GMC’s Clinical Assessment Centre in Manchester.

Conclusion

Preparing for the PLAB Part 1 revision exam is an intensive process that demands a well-structured study plan, reliable resources, and dedicated practice. Begin with a solid understanding of the exam structure, covering all the key specialties through question banks, textbooks, and guidelines. With consistent effort and the right resources, you’ll be well-equipped to approach the exam with confidence.

[topscoree]

The Road to NEET: Your Comprehensive Guide

Preparing for the National Eligibility cum Entrance Test (NEET) marks a crucial milestone for aspiring medical students in India. With intense competition and an extensive syllabus, having a clear strategy is vital for achieving success. This comprehensive guide will outline the key steps and strategies to help you navigate your NEET preparation effectively.

NEET Training in Coimbatore

1. Familiarize Yourself with the NEET Exam Structure

The initial step on your NEET journey is to understand the exam structure. NEET comprises 180 multiple-choice questions (MCQs) across three subjects: Physics, Chemistry, and Biology (which includes Botany and Zoology).

Key Information:

Total Questions: 180

Duration: 3 hours

Scoring: +4 for each correct answer, -1 for each incorrect answer

Getting acquainted with the exam format will enable you to manage your time better and reduce anxiety on exam day.

2. Develop a Comprehensive Study Plan

A well-structured study plan is essential for effectively covering the extensive syllabus. Break each subject into manageable topics and assign specific timeframes for each. Your study plan should ensure a balanced approach across all three subjects while addressing your individual strengths and weaknesses.

Tips for an Effective Study Plan:

Daily Study Goals: Aim for 6-8 hours of focused study each day.

Weekly Assessments: Reserve time to evaluate your progress and make necessary adjustments to your study plan.

Rotate Subjects: Change subjects periodically to keep your study sessions dynamic and reinforce learning.

NEET Coaching in Coimbatore

3. Select the Appropriate Study Materials

Choosing the right study materials can significantly affect your preparation. Invest in high-quality textbooks and reference books that align with the NEET syllabus. The NCERT textbooks are essential, particularly for Biology, while reference books can deepen your understanding of Physics and Chemistry.

Recommended Study Materials:

Physics: “Concepts of Physics” by H.C. Verma, “D.C. Pandey” series

Chemistry: “Physical Chemistry” by O.P. Tandon, “Organic Chemistry” by Morrison and Boyd

Biology: NCERT Biology, “Trueman’s Biology”

4. Prioritize Conceptual Understanding

NEET emphasizes the application of concepts over rote memorization. Focus on grasping the fundamental principles in each subject, as this will prepare you to solve complex problems and application-based questions effectively.

Strategies for In-Depth Learning:

Use Visual Aids: Incorporate diagrams, charts, and videos to clarify complex concepts.

Participate in Study Groups: Collaborate with peers to discuss and reinforce your understanding.

Teach Others: Explaining concepts to peers can enhance your comprehension.

5. Practice Regularly with Mock Tests

Consistent practice is crucial for success in NEET. Taking mock tests simulates the exam experience and helps you evaluate your knowledge and time management skills.

Advantages of Mock Tests:

Identify Weak Areas: Assess your performance to pinpoint topics requiring additional focus.

Get Familiar with Exam Conditions: Practicing under timed conditions prepares you for the actual exam environment.

Build Confidence: The more you practice, the more self-assured you’ll feel on exam day.

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6. Revise Effectively

Revision is vital for reinforcing what you’ve learned. Dedicate specific time each week for revision to solidify your understanding of essential concepts.

Effective Revision Techniques:

Spaced Repetition: Review materials at intervals to improve memory retention.

Summarize Your Notes: Create concise notes or flashcards for quick review sessions.

7. Prioritize Your Health

Prioritizing your physical and mental health is important during NEET preparation. Living a healthy lifestyle will keep you energized and attentive.

Health Tips:

Eat a Balanced Diet: Incorporate nutritious meals rich in vitamins, minerals, and proteins.

Engage in Regular Exercise: Participate in activities like jogging or yoga to alleviate stress.

Ensure Adequate Sleep: Aim for 7-8 hours of sleep each night to keep your mind sharp.

8. Stay Motivated and Positive

Keeping your motivation high throughout NEET preparation can be challenging. Surround yourself with supportive friends and family, and consistently remind yourself of your goals.

Tips for Staying Motivated:

Set Attainable Goals: Break your study sessions into smaller, manageable tasks and celebrate small achievements.

Visualize Your Success: Envision yourself achieving your goal of becoming a doctor to maintain focus on your objectives.

Connect with Others: Join online forums or study groups to share experiences and gain insights.

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Conclusion

The journey to NEET is fraught with challenges, but with the right preparation, you can navigate them successfully and realize your dream of becoming a medical professional. By following this comprehensive guide, you will equip yourself with the tools and strategies necessary for excelling in your NEET preparation. Stay committed, keep a positive attitude, and remember that your hard work will ultimately yield results. Wishing you the best of luck on your path to success! 

[alianoralacanta]

While a lot of this article is very good, the value proposition of radiography presented is incorrect. Professional radiographers will always be needed in part of the process, if only so that the accreditation boards are satisfied appropriate monitoring is in place and to help reassure patients who don't trust computers (a part of the population computer experts often forget to consider). The actual value proposition is to enable each each radiographer to do: - more accurate scans (something that is now the case for white British and USA people, albeit a long way off for everyone else), resulting in more efficient spending downstream (more accurate treatment, with more precision and more confidence). - more total scans (a radiography AI is intended to give results much faster than a human, and in some cases can help the radiographer see what exactly caused the scan to be classified as abnormal. Results on this are mixed). This means radiographers can get through more scans in a day, cutting waiting times and earning more money for the same wage base. In places where there simply aren't enough qualified radiographers to go round, that's a big advantage. - identify patterns within scans that researchers haven't spotted yet. This is both the potential biggest saving and the highest-risk proposition. While AI research is ongoing into this part, it's also the part which has so far revealed zero success. As for the type of bubble this is, I suspect AI is only going to partially explode, because large parts of AI are successfully implementing. You don't hear about how much AI is already integrated into areas like security, energy management and computer game NPC design because these have occurred largely successfully and without causing large media waves. The platform is large enough that some of the large numbers of people skilling in AI will definitely find work in AI after the bubble bursts, and it will be considerably more than before the bubble got going. There is one other promising legacy likely, which is the people who are trying to skill to get into AI generally need a solid base in at least one general programming language in order to make progress with the likes of Tensorflow or Pytorch (Python and C++ are the ones I see recommended most often as methods to learn enough programming for the AI stuff to make sense at a programming level). Python and C++ aren't going away, the number of uses for these that don't involve AI is growing every week, and even people who don't take a career in computing will benefit from the logical thinking that comes from learning a programming language due to something they are interested in (rather than as a rote lesson). A lot of AI is ridiculous. Some of it is worthwhile. We need to make sure the mess from the downfall is not too big, so that computing can build back from a solid base - and be aware AI will definitely be part of that base even if the AI grandees most heard in the press fall.

What kind of bubble is AI?

My latest column for Locus Magazine is "What Kind of Bubble is AI?" All economic bubbles are hugely destructive, but some of them leave behind wreckage that can be salvaged for useful purposes, while others leave nothing behind but ashes:

https://locusmag.com/2023/12/commentary-cory-doctorow-what-kind-of-bubble-is-ai/

Think about some 21st century bubbles. The dotcom bubble was a terrible tragedy, one that drained the coffers of pension funds and other institutional investors and wiped out retail investors who were gulled by Superbowl Ads. But there was a lot left behind after the dotcoms were wiped out: cheap servers, office furniture and space, but far more importantly, a generation of young people who'd been trained as web makers, leaving nontechnical degree programs to learn HTML, perl and python. This created a whole cohort of technologists from non-technical backgrounds, a first in technological history. Many of these people became the vanguard of a more inclusive and humane tech development movement, and they were able to make interesting and useful services and products in an environment where raw materials – compute, bandwidth, space and talent – were available at firesale prices.

Contrast this with the crypto bubble. It, too, destroyed the fortunes of institutional and individual investors through fraud and Superbowl Ads. It, too, lured in nontechnical people to learn esoteric disciplines at investor expense. But apart from a smattering of Rust programmers, the main residue of crypto is bad digital art and worse Austrian economics.

Or think of Worldcom vs Enron. Both bubbles were built on pure fraud, but Enron's fraud left nothing behind but a string of suspicious deaths. By contrast, Worldcom's fraud was a Big Store con that required laying a ton of fiber that is still in the ground to this day, and is being bought and used at pennies on the dollar.

AI is definitely a bubble. As I write in the column, if you fly into SFO and rent a car and drive north to San Francisco or south to Silicon Valley, every single billboard is advertising an "AI" startup, many of which are not even using anything that can be remotely characterized as AI. That's amazing, considering what a meaningless buzzword AI already is.

So which kind of bubble is AI? When it pops, will something useful be left behind, or will it go away altogether? To be sure, there's a legion of technologists who are learning Tensorflow and Pytorch. These nominally open source tools are bound, respectively, to Google and Facebook's AI environments:

https://pluralistic.net/2023/08/18/openwashing/#you-keep-using-that-word-i-do-not-think-it-means-what-you-think-it-means

But if those environments go away, those programming skills become a lot less useful. Live, large-scale Big Tech AI projects are shockingly expensive to run. Some of their costs are fixed – collecting, labeling and processing training data – but the running costs for each query are prodigious. There's a massive primary energy bill for the servers, a nearly as large energy bill for the chillers, and a titanic wage bill for the specialized technical staff involved.

Once investor subsidies dry up, will the real-world, non-hyperbolic applications for AI be enough to cover these running costs? AI applications can be plotted on a 2X2 grid whose axes are "value" (how much customers will pay for them) and "risk tolerance" (how perfect the product needs to be).

Charging teenaged D&D players $10 month for an image generator that creates epic illustrations of their characters fighting monsters is low value and very risk tolerant (teenagers aren't overly worried about six-fingered swordspeople with three pupils in each eye). Charging scammy spamfarms $500/month for a text generator that spits out dull, search-algorithm-pleasing narratives to appear over recipes is likewise low-value and highly risk tolerant (your customer doesn't care if the text is nonsense). Charging visually impaired people $100 month for an app that plays a text-to-speech description of anything they point their cameras at is low-value and moderately risk tolerant ("that's your blue shirt" when it's green is not a big deal, while "the street is safe to cross" when it's not is a much bigger one).

Morganstanley doesn't talk about the trillions the AI industry will be worth some day because of these applications. These are just spinoffs from the main event, a collection of extremely high-value applications. Think of self-driving cars or radiology bots that analyze chest x-rays and characterize masses as cancerous or noncancerous.

These are high value – but only if they are also risk-tolerant. The pitch for self-driving cars is "fire most drivers and replace them with 'humans in the loop' who intervene at critical junctures." That's the risk-tolerant version of self-driving cars, and it's a failure. More than $100b has been incinerated chasing self-driving cars, and cars are nowhere near driving themselves:

https://pluralistic.net/2022/10/09/herbies-revenge/#100-billion-here-100-billion-there-pretty-soon-youre-talking-real-money

Quite the reverse, in fact. Cruise was just forced to quit the field after one of their cars maimed a woman – a pedestrian who had not opted into being part of a high-risk AI experiment – and dragged her body 20 feet through the streets of San Francisco. Afterwards, it emerged that Cruise had replaced the single low-waged driver who would normally be paid to operate a taxi with 1.5 high-waged skilled technicians who remotely oversaw each of its vehicles:

https://www.nytimes.com/2023/11/03/technology/cruise-general-motors-self-driving-cars.html

The self-driving pitch isn't that your car will correct your own human errors (like an alarm that sounds when you activate your turn signal while someone is in your blind-spot). Self-driving isn't about using automation to augment human skill – it's about replacing humans. There's no business case for spending hundreds of billions on better safety systems for cars (there's a human case for it, though!). The only way the price-tag justifies itself is if paid drivers can be fired and replaced with software that costs less than their wages.

What about radiologists? Radiologists certainly make mistakes from time to time, and if there's a computer vision system that makes different mistakes than the sort that humans make, they could be a cheap way of generating second opinions that trigger re-examination by a human radiologist. But no AI investor thinks their return will come from selling hospitals that reduce the number of X-rays each radiologist processes every day, as a second-opinion-generating system would. Rather, the value of AI radiologists comes from firing most of your human radiologists and replacing them with software whose judgments are cursorily double-checked by a human whose "automation blindness" will turn them into an OK-button-mashing automaton:

https://pluralistic.net/2023/08/23/automation-blindness/#humans-in-the-loop

The profit-generating pitch for high-value AI applications lies in creating "reverse centaurs": humans who serve as appendages for automation that operates at a speed and scale that is unrelated to the capacity or needs of the worker:

https://pluralistic.net/2022/04/17/revenge-of-the-chickenized-reverse-centaurs/

But unless these high-value applications are intrinsically risk-tolerant, they are poor candidates for automation. Cruise was able to nonconsensually enlist the population of San Francisco in an experimental murderbot development program thanks to the vast sums of money sloshing around the industry. Some of this money funds the inevitabilist narrative that self-driving cars are coming, it's only a matter of when, not if, and so SF had better get in the autonomous vehicle or get run over by the forces of history.

Once the bubble pops (all bubbles pop), AI applications will have to rise or fall on their actual merits, not their promise. The odds are stacked against the long-term survival of high-value, risk-intolerant AI applications.

The problem for AI is that while there are a lot of risk-tolerant applications, they're almost all low-value; while nearly all the high-value applications are risk-intolerant. Once AI has to be profitable – once investors withdraw their subsidies from money-losing ventures – the risk-tolerant applications need to be sufficient to run those tremendously expensive servers in those brutally expensive data-centers tended by exceptionally expensive technical workers.

If they aren't, then the business case for running those servers goes away, and so do the servers – and so do all those risk-tolerant, low-value applications. It doesn't matter if helping blind people make sense of their surroundings is socially beneficial. It doesn't matter if teenaged gamers love their epic character art. It doesn't even matter how horny scammers are for generating AI nonsense SEO websites:

https://twitter.com/jakezward/status/1728032634037567509

These applications are all riding on the coattails of the big AI models that are being built and operated at a loss in order to be profitable. If they remain unprofitable long enough, the private sector will no longer pay to operate them.

Now, there are smaller models, models that stand alone and run on commodity hardware. These would persist even after the AI bubble bursts, because most of their costs are setup costs that have already been borne by the well-funded companies who created them. These models are limited, of course, though the communities that have formed around them have pushed those limits in surprising ways, far beyond their original manufacturers' beliefs about their capacity. These communities will continue to push those limits for as long as they find the models useful.

These standalone, "toy" models are derived from the big models, though. When the AI bubble bursts and the private sector no longer subsidizes mass-scale model creation, it will cease to spin out more sophisticated models that run on commodity hardware (it's possible that Federated learning and other techniques for spreading out the work of making large-scale models will fill the gap).

So what kind of bubble is the AI bubble? What will we salvage from its wreckage? Perhaps the communities who've invested in becoming experts in Pytorch and Tensorflow will wrestle them away from their corporate masters and make them generally useful. Certainly, a lot of people will have gained skills in applying statistical techniques.

But there will also be a lot of unsalvageable wreckage. As big AI models get integrated into the processes of the productive economy, AI becomes a source of systemic risk. The only thing worse than having an automated process that is rendered dangerous or erratic based on AI integration is to have that process fail entirely because the AI suddenly disappeared, a collapse that is too precipitous for former AI customers to engineer a soft landing for their systems.

This is a blind spot in our policymakers debates about AI. The smart policymakers are asking questions about fairness, algorithmic bias, and fraud. The foolish policymakers are ensnared in fantasies about "AI safety," AKA "Will the chatbot become a superintelligence that turns the whole human race into paperclips?"

https://pluralistic.net/2023/11/27/10-types-of-people/#taking-up-a-lot-of-space

But no one is asking, "What will we do if" – when – "the AI bubble pops and most of this stuff disappears overnight?"

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/12/19/bubblenomics/#pop

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

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

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tom_bullock (modified) https://www.flickr.com/photos/tombullock/25173469495/

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[crystalconfusions]

i feel like i have improved a ton in japanese, but the more i learn the more i am confronted with my own inadequacy...

ive improved a lot in listening and i can understand a good amount (although not everything obviously), but my speaking ability is dogshit. i get a good amount of chances to speak japanese living in japan, but its mostly all the same surface level topics like grocery store, 'its hot/cold/rainy' etc. and when anything other than those rote topics is brought up, i have a sub-toddler level of speaking. like i just say disjointed incorrect individual words with shit grammar. its so annoying bruhhhhhh

i wish i had an opportunity outside of work or basic interactions to talk in japanese with ppl, but no one wants to hang out with me bc my japanese is so shitty lmao. ik its not just that or even that at all, but ppl have their own lives and im just a disruption to a certain extent. not being able to speak well rlly limits my ability to socialize outside of the foreigner groups around me, but then i cant improve either bc theres no one i can rlly speak japanese with. this is also made worse by the fact that there are pretty much 0 ppl in my town that are my age, and those that are like 2-3 years older than me are all teachers who i work with lmaooo. not even getting into the limiting of options bc ppl are weird about opposite gender friendships here.

overall the guy ive had the most in depth convos with in japanese is the guy who owns the fucking liquor store i go to regularly, and he just talks to me bc hes impressed by my drinking capacity... not a good sign? lol