ToI's Analysis of Medical College Admissions in 2017

I am not thrilled to see the word "merit" being used so casually, but Rema Nagarajan's ToI news story captures the essence in its title: Money, not quota, dilutes merit in medical admissions:

It is not caste-based reservation but money that compromises merit in medical admissions.

This is obvious from the difference of about 140 marks, or close to 20 percentage points, between the average NEET scores of admissions to over 39,000 government-controlled seats and those to the over 17,000 management and NRI quota seats in private colleges where fees determine admission.

TOI analysed details of nearly 57,000 students admitted to 409 colleges last year. The average NEET score of students in government-controlled seats was 448 out of 720, while the quotas under private control averaged just 306.

Incidentally, the average score of students admitted under the SC quota in government colleges was 398 and the overall average for SC students in all colleges was 367, both much higher than the overall average for privately controlled seats.

Links

Two links [hat tip to M. Madhan]:

• Ben Guarino, Emily Rauhala and William Wan in The Washington Post: Health & Science China increasingly challenges American dominance of science

  The United States spends half a trillion dollars a year on scientific research — more than any other nation on Earth — but China has pulled into second place, with the European Union third and Japan a distant fourth.

  China is on track to surpass the United States by the end of this year, according to the National Science Board. In 2016, annual scientific publications from China outnumbered those from the United States for the first time.

  “There seems to be a sea change in how people are talking about Chinese science,” said Alanna Krolikowski, a Chinese science expert at Missouri University of Science and Technology. Foreign observers, many of whom were once condescending, now “are rather in awe at what the Chinese policies have accomplished.”

• Dalmeet Singh Chawla in Nature Index: Italian scientists increase self-citations in response to promotion policy:

  Italian scientists have been citing themselves more often since a controversial law came into effect in 2010 demanding academics meet productivity thresholds to gain promotion. Economic and managerial engineering showed the greatest leap in self-citations from 2010 to 2014 of the four fields examined.

What if Facebook was actually called Policebook?

Apparently, a serial murderer and rapist was identified by the police when they used a DNA database (called GEDmatch, which appears to be a site meant for helping people find their relatives) to which he had voluntarily provided his DNA data. Science has an interview with Yaniv Erlich, a Columbia University geneticist, who had alerted to possible uses of a site such as GEDmatch in 2014.

An excerpt where Erlich makes a key point:

Q: There’s a lot of concern about privacy being compromised here, but people voluntarily put their data into GEDmatch.

A: It's not like people fully understand the consequences of putting their DNA into a public database. They think, “So many people use the website, so it’s OK.” Or: “Oh, it’s a website for genealogy.” What if it was called Police Genealogy? People wouldn’t do it. We don’t think about everything. We think about the most likely thing. [Bold emphasis added]

Avijit Pathak: "Debating Plagiarism: Indian Academia Is Producing Imitative Conformists"

Riffing off on recent cases of plagiarism by Indian academics, he poses a deeper question: "Is ... our thinking itself ... plagiarised?"

To illustrate his point, he presents an episode from his own days "as a student of sociology at a leading university in Delhi":

... Let me recall what I experienced as a student of sociology at a leading university in Delhi. My professor asked me to write a paper on caste. I met my professor and conveyed my wish. ‘Sir, I have read what you have asked us to read. However, in my paper I wish to write something more: the way I saw, experienced and analysed the institutionalisation and practice of caste, and through this account, I would learn and unlearn the texts you have suggested.’

The professor said, ‘No, you can’t write what you think, experience and feel. You are required to write the way the likes of M.N. Srinivas and Louis Dumont have thought about it’.

I followed his instruction and wrote a highly-mechanised but ‘academically impressive’ paper with predictable quotes and references from the big names. Needless to add, I got a good grade. In other words, I got the message: My style, my perception, my words do not count; what matters is a defined academic format, a style created by others. I have to be clever in the art of copying.

Economics Job Market

I first learned about it -- the economics job market which happens during the annual meeting of AEA, the American Economic Association -- from this post by Noah Smith, and I found the whole thing fascinating [I am always interested in disciplinary subcultures -- like the importance of conference papers in Computer Science, or the alphabetical listing of authors in certain disciplines].

But you must listen to this fantastic Planet Money (on NPR) story what this job market does, and how it goes about it -- from the point of view of one of the job applicants (a truly brave soul -- right through the podcast, I was seriously rooting for him!) and of several employers. Absolutely fabulous!

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Hat tip to Econ Nobel Prize winner Alvin Roth, who is also interviewed in the Planet Money story.

If lack of reproducibility is a crisis, so is lack of producibility

The accepted practice is instead to adjust the model so that it continues to agree with the lack of empirical support.

This very Zen statement is a part of a commentary by theoretical particle physicist Sabine Hossenfelder-- in Nature, no less (so it must be fashionable, if not also true) -- who writes candidly about the crisis in her field (and its neighbours: astrophysics and cosmology): Science needs reason to be trusted [Caution: paywall]. She calls it a crisis of "overproduction" (i.e., abundance) of theories, but I like to think of it as a crisis of "producibility" of experimental data.

In recent years, trust in science has been severely challenged by the reproducibility crisis. This problem has predominantly fallen on the life sciences where, it turns out, many peer-reviewed findings can't be independently reproduced. Attempts to solve this have focused on improving the current measures for statistical reliability and their practical implementation. Changes like this were made to increase scientific objectivity or — more bluntly — to prevent scientists from lying to themselves and each other. They were made to re-establish trust.

The reproducibility crisis is a problem, but at least it's a problem that has been recognized and is being addressed. From where I sit, however, in a research area that can be roughly summarized as the foundations of physics — cosmology, physics beyond the standard model, the foundations of quantum mechanics — I have a front-row seat to a much bigger problem.

I work in theory development. Our task, loosely speaking, is to come up with new — somehow better — explanations for already existing observations, and then make predictions to test these ideas. We have no reproducibility crisis because we have no data to begin with ... [Bold emphasis added]

Here's something that will makes your jaw not just drop, but go into a tailspin:

In December 2015, the LHC collaborations CMS and ATLAS presented evidence for a deviation from standard-model physics at approximately 750 GeV resonant mass2, 3. The excess appeared in the two-photon decay channel and had a low statistical significance. It didn't look like anything anybody had ever predicted. By August 2016, new data had revealed that the excess was merely a statistical fluctuation. But before this happened, high-energy physicists produced more than 600 papers to explain the supposed signal. Many of these papers were published in the field's top journals. None of them describes reality.

How good are graduate admission interviews, if job interviews are "utterly useless"?

Faculty members in almost all the Indian institutions are getting ready to interview tens (if not hundreds) of students for a handful (or a few handfuls) of PhD slots in their departments. A recent NYTimes article urges us to be mindful of limitations of this format: The Utter Uselessness of Job Interviews by Jason Dana.

I realize there are quite a few differences between the kind of interviews Dana describes in his article and the kind we use. For example, his "experimental" interviews were (probably) unstructured, while we may be using something more structured [such as probing candidates specifically in the areas / subfields they say they are strong in]. Also, given the overwhelmingly large number of candidates compared to the number of available slots, there's usually a pre-screening exercise which relies on previous academic record, research experience, scores / ranks in entrance exams, etc.

And yet, this article reminds us some of the pitfalls of the interview process.

"Removing Morons from the Productive Flow"

This profile of Scott Adams, the genius who created the Dilbert comics, has its focus elsewhere (his rationalizations of the rise and rise of Donald Trump during the US Presidential primaries and election), but somewhere in the middle is this gem (in bold, below) [If you are wondering why it stuck a chord, you haven't seen this ... (;-)]:

Adams’s Dilbert empire has been growing for three decades. When he launched the strip in the late ’80s, long-running staples such as Dennis the Menace, Family Circus, and Blondie seemed saccharine and dated. Adams’s creation was fresh, starring a sardonic software engineer named Dilbert; his conceited and grandiose dog, Dogbert; an incompetent boss; and a host of odd co-workers. Early installments showed Dilbert at home. When Adams refocused the strip on the workplace, it caught fire among a generation of office drones who spent their days staring at spreadsheets and slide decks. While workers had long tacked comics like The Far Side and Cathy to their felt cubicle walls, to say something about themselves and their brand of humor, here was a subversive comic about cubicle culture itself. During the ’90s, amid waves of corporate downsizing and the tech boom, a zeitgeisty Dilbert graced the covers of Newsweek, Time, and Fortune. Adams churned out Dilbert-themed calendars, knickknacks, and even a TV show. He also penned op-eds and business tomes, including The Dilbert Principle, based on the theory that companies tend to promote their least competent employees to middle management, “removing morons from the productive flow.”

* * *

Update: Wikipedia has an entry on the Dilbert Principle, in case you are interested.

Links

1. What if Sociologists Had as Much Influence as Economists? | The Upshot | Neil Irwin [See also: Is ethnography the most policy-relevant sociology? | Fabio Rojas]

2. ‘Copy and paste’ content spotted in IISER Thiruvananthapuram director’s papers | Journo's Diary | R. Prasad

In other words, "Get a Life"

Very little has been written on jealousy in academic life, and yet, anecdotal evidence suggests that it is prevalent in our profession. This is unsurprising. As Chronicle readers are well aware, academe today is a place of increasingly precarious employment conditions — where the "publish or perish" mantra is more relevant than ever and the pressure to win grant money has reached fever pitch.

In such an environment, it’s little wonder that jealousy can take hold. I’ve certainly felt my share (and I herewith apologize for privately cursing those of you who got positions and/or book contracts that I wanted). Jealousy may come with the academic turf but that’s rarely a good thing. So what can we do to better manage our envy at all stages of the academic career?

That's from Jay Daniel Thompson in The Chronicle of Higher Educationn: Maybe You’re Just a Jealous Academic. Can you spot the understatement of 2017? Hint: it's in bold.

This article eventually gets to "self-help" domain of how to deal with jealousy of the academic kind, and has an advice-list that might help you cope. The last piece of advice? "Develop interests outside the academy." In other words, "Get a Life".

Links

• Christian Catalini, Christian Fons-Rosen, and Patrick Gaulé in Vox.eu: Cheaper flights and scientific collaboration

• Noah Smith in Noahpinion: Do economists have physics envy? (Part 2).

• Maria Konnikova in New Yorker: Practice Doesn't Make Perfect.

• Rhaina Cohen in The Atlantic: What Programming's Past Reveals About Today's Gender Pay Gap.

• Gina Kolata in NY Times: Lost in Academia: So Many Research Scientists, So Few Openings as Professors.

Links: Tim Hunt Edition

1. Maki Naro in Popular Science: The trouble with Nobel Prizes -- They're not magic medals of blamelessness.

   So don't write to me saying I don't care about science because a poor guy tarnished his own gold star by making a bad, sexist joke and got called out on it. Instead, ask yourself how much you care about science that you've allowed the past to supersede the future. Take a long look at the choices that led you to put science before people. Instead of blindly defending an old man with a medal, try to listen and reflect upon yourself and the society that led you to defend him in the first place. Then GTFO.

2. Alice Bell at Open Democracy: After Tim Hunt: Another Science is Possible. "After the widespread reaction to Tim Hunt’s comments on women in science, it’s time to unpick the various hierarchies that stifle scientific debates and practice."

3. Janet Stemwedel at the Forbes Science Blog: What if Tim Hunt had done it differently:

   So, let’s rewind the universe to a point in time before Tim Hunt’s trajectory intersected with the controversy. You might think the crucial moment at which to consider “what if” is when Hunt was asked to make some remarks to the luncheon. But let’s go back more than a year earlier, to spring of 2014, when Tim Hunt was interviewed for Lab Times. Here’s part of that published exchange:

   In your opinion, why are women still under-represented in senior positions in academia and funding bodies?

   Hunt: I’m not sure there is really a problem, actually. People just look at the statistics. I dare, myself, think there is any discrimination, either for or against men or women. I think people are really good at selecting good scientists but I must admit the inequalities in the outcomes, especially at the higher end, are quite staggering. And I have no idea what the reasons are. One should start asking why women being under-represented in senior positions is such a big problem. Is this actually a bad thing? It is not immediately obvious for me… is this bad for women? Or bad for science? Or bad for society? I don’t know, it clearly upsets people a lot.

   What if, after the interview, Tim Hunt had done some thinking about the underrepresentation of women in science, especially in senior positions? What if he had sought out some of the people clearly upset by the inequalities in outcomes and listened to them in order better to understand that upset? What if he had looked at the research on the various factors that still present barriers to entry and inclusion for women (among others) in science?

   If he had done that, then by June of 2015, asked to speak at the luncheon, he might have had a somewhat better understanding of the women scientists in his audience.

LInks

1. Carnegie Mellon Reels After Uber Lures Away Researchers (Mike Ramsey and Douglas Macmillan in WSJ)

2. Deepak Singh in The Atlantic: 'I've Never Thanked My Parents for Anything'. "In America, saying thank you is routine. In India, it can be insulting."

3. Chris Woolston in Nature: Fruit-fly paper has 1,000 authors "Genomics paper with an unusually high number of authors sets researchers buzzing on social media." See also a related story from physics.

4. The Economist: Keeping it on the company campus. "As more firms have set up their own “corporate universities”, they have become less willing to pay for their managers to go to business school."

5. A picture gallery on 150 years of mathematics in the UK in The Guardian

Computer Science, Women, NYTimes!

NYTimes has yet another story on how some college or the other is doing such a great job of attracting, and retaining, women in its computer science program. If it is the University of Washington this time, it was Harvey Mudd last year, and Carnegie Mellon back in 2007. These are the ones I have read; there may be others that I didn't even know about. [Update: And, oh, there's also this from 2011, though it is not quite about women in computer science].

It would have been interesting if the later stories showed some awareness of the earlier ones -- for example, if Carnegie Mellon did some great things get a lot more women into its computer science program back in 2007, how well is it doing now? Has it improved enrollment figures for women even further? Has it hit a wall? Has it let things slide?

But, but ... I'm just quibbling here. The most recent intervention by NYTimes in the Women-in-Computer-Science debate is quite good in its coverage of the kinds of experiments at different places (UWashington, Michigan State, Harvey Mudd, Harvard, ...), as well as of the kinds of curriculum-related debates within Computer Science.

Doing Science is, in fact, "Rocket Science"

Leonard Mlodinov has an op-ed in NYTimes arguing against the myth that science is just a series of flashes of intuitive insights that just hit people by accident.

Two thousand years ago, Aristotle’s “Physics” was a wide-ranging set of theories that were easy to state and understand. But his ideas were almost completely wrong. Newton’s “Principia” ushered in the age of modern science, but remains one of the most impenetrable books ever written. There is a reason: The truths of nature are subtle, and require deep and careful thought.

Over the past few centuries we have invested that level of thought, and so while in the 19th century the Reuters news service used carrier pigeons to fly stock prices between cities, today we have the Internet.

Even if we are not scientists, every day we are challenged to make judgments and decisions about technical matters like vaccinations, financial investments, diet supplements and, of course, global warming. If our discourse on such topics is to be intelligent and productive, we need to dip below the surface and grapple with the complex underlying issues. The myths can seduce one into believing there is an easier path, one that doesn’t require such hard work.

But even beyond issues of science, there is a broader lesson ... We all run into difficult problems in life, and we will be happier and more successful if we appreciate that the answers often aren’t quick, or easy.

Links: Women in Science Edition

1. Toni Schmader, Jessica Whitehead, and Vicki H. Wysocki: A Linguistic Comparison of Letters of Recommendation for Male and Female Chemistry and Biochemistry Job Applicants.

   Letters of recommendation are central to the hiring process. However, gender stereotypes could bias how recommenders describe female compared to male applicants. In the current study, text analysis software was used to examine 886 letters of recommendation written on behalf of 235 male and 42 female applicants for either a chemistry or biochemistry faculty position at a large U.S. research university. Results revealed more similarities than differences in letters written for male and female candidates. However, recommenders used significantly more standout adjectives to describe male as compared to female candidates. Letters containing more standout words also included more ability words and fewer grindstone words. Research is needed to explore how differences in language use affect perceivers’ evaluations of female candidates.

2. Joan C. Williams in HBR: The 5 Biases Pushing Women Out of STEM.

3. Jessica Collett at Scatterplot: Feeling Like a Fraud? You Are Not Alone. A summary of her recent research on the impostor syndrome.

4. Noah Smith in Bloomberg: Bigotry Is Expensive.

   So if a society bases its decisions of who gets which job on race and gender, it’s going to be sacrificing efficiency. If women aren’t allowed to be doctors, the talent pool for doctors will be diluted, and wages will be pushed up too high, choking off output. This would be true even in a bizarro world where every man was a better doctor than every woman! Of course that’s not even remotely true, but the point is, the theory of comparative advantage doesn’t care about average differences in absolute ability. If you’re making rules about which type of people are allowed to do which type of job, you’re hurting the economy.

   Just how big of a difference does this make? A team of top economists has recently studied the question, and their results are pretty startling. In “The Allocation of Talent and Economic Growth,” economists Chang-Tai Hsieh and Erik Hurst of the University of Chicago Booth Business School and Charles Jones and Peter Klenow of Stanford estimate that one fifth of total growth in U.S. output per worker between 1960 and 2008 was due to a decline in discrimination.

Links

1. Michael Gordin in Aeon: Absolute English. "How did science come to speak only English?"

2. Noah Berlatsky in Pacific Standard: What Is the Point of Academic Books? "Ultimately, they're meant to disseminate knowledge. But their narrow appeal makes them expensive to produce and harder to sell."

3. Gillian Tett in The Financial Times: A degree of creativity. ‘Vocational degrees provide skills that can become outdated or be replaced by robots.’

4. Attention Decay in Science, a paper by Pietro Della Briotta Parolo, Raj Kumar Pan, Rumi Ghosh, Bernardo A. Huberman, and Kimmo Kaski. Here's the abstract:

   The exponential growth in the number of scientific papers makes it increasingly difficult for researchers to keep track of all the publications relevant to their work. Consequently, the attention that can be devoted to individual papers, measured by their citation counts, is bound to decay rapidly. In this work we make a thorough study of the life-cycle of papers in different disciplines. Typically, the citation rate of a paper increases up to a few years after its publication, reaches a peak and then decreases rapidly. This decay can be described by an exponential or a power law behavior, as in ultradiffusive processes, with exponential fitting better than power law for the majority of cases. The decay is also becoming faster over the years, signaling that nowadays papers are forgotten more quickly. However, when time is counted in terms of the number of published papers, the rate of decay of citations is fairly independent of the period considered. This indicates that the attention of scholars depends on the number of published items, and not on real time.

Bob Goldstein: The Thrill of Defeat

In Nautilus, he tries very hard, perhaps too hard, to convince us that people whose research gets scooped would always feel bad -- horribly, horribly bad; his article has quite a few sentences like this one: "Months or years of work can become redundant, or worthless." He then goes on to show that the reaction of Francis Crick and Sidney Brenner was totally the opposite of sadness or bitterness. Maybe this is some sort of a narrative ploy to make Crick and Brenner look more noble and almost superhuman (which they probably are!).

The rest of the story is quite good, actually. Along the way, you get some interesting science as well (and some inside dope about how the biochemists and geneticists hated each other).

Anyways, here it is:

Crick would later write that the audience in Moscow had been “electrified” by Nirenberg’s result, changing the word later to “startled.” Crick may have felt both startled and electrified. But disappointment? If Crick felt some disappointment, it wasn’t apparent to Meselson, who characterized Crick’s initial reaction to the news as “joy.” “What else could it be?,” Meselson explained to me by phone, “by god, we’d know the answer in our lifetime!”

Even Meselson, who had his own research program on DNA, had impulsively hugged Nirenberg at the end of his talk. I tried to imagine two men of that era spontaneously hugging in a lecture room at a conference, particularly when one was a geneticist and other a biochemist. Maxine Singer, a biochemist who gave Nirenberg the RNAs he needed for his experiments, told me that the “biochemists and geneticists were suspicious of each other,” something that Brenner echoed to me in person.

Links

1. Harvard University press release: Cooperation, considered. "New model reveals how motives can affect cooperation". This is based on an interesting game -- a variation of the cooperation game by adding a twist that conveys some information about the first player's motives to the second player.

2. Emily Singer in Quanta: Game Theory Calls Cooperation Into Question. "A recent solution to the prisoner’s dilemma, a classic game theory scenario, has created new puzzles in evolutionary biology."

3. Clive Thompson in Smithsonian: How the Photocopier Changed the Way We Worked—and Played. A very interesting excerpt about how the US lawmakers viewed "xeroxing":

   “It was really a great moment in the late ’70s when it was a wonderful loosening of copyright,” says Lisa Gitelman, professor of English and media studies at New York University. These days, Congress is working hard­—often at the behest of movie studios or record labels—in the opposite direction, making it harder for people to copy things digitally. But back in the first cultural glow of the Xerox, lawmakers and judges came to the opposite conclusion: Copying was good for society.

Links

1. The Caravan: No double entendres: The words the censor board doesn't want you to hear (discretion advised).

2. Robert Frank in Vox: Why have weddings and houses gotten so ridiculously expensive? Blame inequality.

3. Paul Krugman: Floor Waxes, Dessert Toppings, and Blogging.