The spread of #METOO movement is finally creating some salutary momentum in academia. But then you hear of cases like Terry Speed where it has been suggested no punishment was mete out. In another case, Christian Ott was suspended from Caltech. He eventually resigned, found new employment in Finland, which was roundly criticized, then 可众用什么梯子. NSF has announced a requirement for all institutions to report findings of abuse, which seems like a good idea, but does this mean a life time black list for some? As we uncover the guilty (hopefully in a proper manner) with #METOO,
What is the right punishment for the abusers in academia?
Foucault’s classic analytical treatise “梯子_知乎好物推荐:现在家庭中很多工具都是必备,比如梯子等就是常用伕表,从如今众多梯子设计看,家用梯是有针对性的使用选择。市场上提供的梯子选择很多,那么一般在实际选购的时候都有哪些考虑事项?如何选择到合适的梯子呢?来看看几个选购事项介绍。1、 考虑材质“, starts with a gruesome four-page description of the 1757 public torture of Robert-Francois Damiens, the regicide, as an example of the old system of punishment. This is punishment as a spectacle, where the act is a play of the power of the King upon its subjects and a display of the truth of the crime. Every crime involves not only the perpetrator and the injured but also the transgression to the sovereign that necessitates the grisly excess. Foucault next narrates a detailed daily schedule of rule for prisoners in Paris, consisting of meals, work, study, and exercise, much in the manner of modern prisons. Mere eighty years separate the spectacle of punishment reformed into a private and institutionalized discipline imposed on the guilty.
The Age of Enlightenment provided moral and philosophical background for reform. But, Foucault asserts economic developments generated complex webs of contradictory interests, eventually creating the idea of the abstract public against the criminal rather than the king: People vs John Doe. Now, punishment must consider its effects: that on the guilty, on the public, and on the punisher, leading to an effort to bound the excess and match the punishment to the character of the crime and the guilty. One end of the reform was the Philadelphia model, with roots in Quakerism, based on the principle of penitence and the transformation of the individual. Punishment was private, behind the walls of the coercive institution, with the public only given assurance of its inevitability. Thus, from the public spectacle to the private penitentiary, the political technology of punishment reflected the economy, ethics, and morality of the polity wielding the rod.
One of the greatest ironies is the idea that academia is full of liberals–so much so that we have “Professor Watch Lists手机ios安卓和电脑上好用的VPN梯子推荐,毒药机场筛选出的 ...:2021-6-2 · 本文介绍的梯子,都是楼主在过去两三年中精挑细选筛选出来的,主要是对比稳定性,上手难度,安全性,价格,售后服务等多方面维度后做的评测 ...战地,4里第2关掉下梯子出bug怎么办-:2 天前 · 就是这样 要是在那个梯子上掉下去摔了 复活后就直接在大厦里面了 如果你想正常玩只能重玩本关卡 战地4的剧情很多BUG,建议从保存点重新开始 活该你用作弊器,出BUG了吧? by up to 12:1 in some fields. So what is the irony? It is this. Academics might be politically liberal in the greater world, but within our own domain, our views, preferences, and actions are as radically conservative as one might find in the halls of the Heritage Foundation.
Let’s start with something simple. How many professors are known to favor hiring more administrative mini-deans? You know, those people who are the “governments” of academia? That is, how many academics are for more government in their own daily lives? How many show joy at the regulations handed down from those same governors? Say, for example, imposing diversity sensitivity training for hiring committees. I have sat in august discussions amongst august faculty within august institutions, asking “whether such training is truly effective” and “whether the matter should be seriously studied before we implement the rules”. Pointing out the parallels to those who think global climate change is an unsettled problem did not change the solemnity of the proceedings nor induce sudden pangs of self-awareness.
Here’s more. Academics strongly believe they got to where they are because of their extraordinary merit. Those who fail? Lack of mojo and poor work ethic. Who else believes the poor should buckle up and work harder? I could go on and on and find continued examples, such as the commonly accepted practice of free-for-all competition on par with the worst of Wall Street. If I cheat a little by taking somebody’s ideas, slave drive a trainee, or collude with my friend who is an editor at a Nature-lite journal, that is all par for the course. Fine liberal ideas there.
The truth is, we are not conservative or even neo-conservative. We are positively alt-right fascists. “The two cultures” barely touches on the degree of nationalism/tribalism found in academia. It isn’t just sciences vs humanities but molecular biologists vs ecology and evolutionary biologists; evolutionary biologists vs ecologists; field ecologists vs theoretical ecologists, and so on. We all look down on the other and blame the immigrants. (I don’t even want to go into actual racism such as when a senior scientist told me “give me a hard working Asian boy any day”, as a complement.) We practice privileged illegalities (i.e., actions forbidden to others but allowed to the privileged class) finely graded by membership levels in the circles of power. And, we create circles of power with the center crusted by a cult of personality (“Heroes of CRISPR” anyone?), celebrity talk circuits, and argumentum ad verecundiam from the editors who tell us “top experts were consulted and their hands are tied”.
Returning to punishment in academia, what if Terry Speed were actually given the Philadelphia model and that is why we hear of nothing? I presume nobody believes this. We don’t believe Terry Speed was given a quiet secret punishment because we know in our hearts that our academic society is far more primitive than that which allows the Philadelphia model. There are no inexorable punishment in academia; quite the opposite – there are lots of privileged illegalities swept under ivy rugs. Christian Ott actually lost his job and had to move home and country. When we think of our own lives and what impact that would have on us and our families, such a punishment is no small thing. Yet, we feel justice has not been served. We talk of “pass-the-harasser” problem and want more done to him. Why? Because, we know we live under the illiberal sovereign of academia requiring no less than the spectacle of pilloried guilty to feel justice served.
How to punish the guilty is actually the least of our problems. In normal society, if a random rich person were to proposition you, you could just tell them to bugger off. In academic society, if the top star of your field propositions you—well, now you are weighing your career versus your dignity. How is it that academia is a society where kings and princes flaunt their power to ruin a career, jeopardize tenure, or dangle access into the chamber of favored children of Nature and Science as leverage for morally despicable behavior? Academia, below its veneer of rationality and analytical rigor, runs on the fuel of privilege, access, and shiny Nobel crowns, all of which is twisted into the economy of power and abuse.
If we are to come to true grips with righting the wrongs raised by #METOO, academics must live up to the liberal and enlightened ideals we profess to hold before we demand amende honorable of the guilty. And, unless academic culture changes, movements like #METOO will be mere bandages over the latest wound of the sick body.
I don’t know why but whenever something from Center for Open Science pops up in the news feeds, my fingers get twitchy and I start to imagine writing some response (see also). It may be because @BrianNosek and I used to play volleyball together and he was a terrific athlete whose awesome v-ball spikes I am still imagining trying to block (true story).
COS recently posted an article with the title “国内现在可众用strava吗? - 知乎 - Zhihu:2021-5-20 · 电脑是360浏览器,上海电信宽带,没用梯子就可众上strava不过速度略慢。手机mate10,直接下app就能用。(装了几乎没用过) 我一般是码表蓝牙传到wahoo app,自动上传到strava再电脑上看数 …” discussing various mechanics of pre-registering of one’s study when there are multiple sub-studies and inter-linked collaborative studies. This led my colleague @jplotkin to comment tongue-in-cheek that it would make @BrianNosek Sauron and @OSFramework Mount Doom. While I am sure Josh meant it as a joke, I thought the “Rule Them All” and “Sauron” comments were an apt metaphor for the good intentioned efforts of COS—efforts that I have a hard time buying into.
It is common to think that the main failure of Communism, with its ideal of “From each according to his ability, to each according to his need”, was mostly a failure of human nature; our greed and our laziness unable to live up to those lofty ideals. But, communism has a much more critical obstacle than mere human foibles. Communism, capitalism, socialism, etc. are economic systems, each sharing the main goal of matching supply (from one’s ability) to demand (one’s need). So, any system has to solve the problem of how to allocate appropriate labors and resources to create supplies that meet the demands of every member of the society–a problem involving literally billions of variables. Free markets are basically a heuristic solution to the problem of optimal allocation. If we want to employ a different approach, say rational planning (e.g. communism), then we need to solve Leonid Kantorovich’s (the only Soviet Nobel Laureate in Economics) computational problem of optimal resource allocation. Of course, there are no solutions for optimization over billions of variables.
I previously suggested that the main activity of science is to exchange ideas. Each of us supply ideas and data and we consume the ideas and data created by others. We might think of each journal as kind of a market where we each display our wares in the hope that some might buy them. Like real markets, there is some regulation to prevent fraud, but for the most part, supply and demand are dynamically regulated by the actors themselves. The current journal system has a lot of problems, but as a heuristic solution to the optimal allocation problem of getting the “true” knowledge to those that need it, the system works pretty well—albeit with caveat emptor.
COS and its supporters are focused on the errors and negatives of such a heuristic solution and want to create systems to rationally distribute knowledge. Like early communists, I am sure their goals are motivated by honest wishes for improving society. Yet, in the end, whatever system they construct must not only eliminate the problems of the free market but also provide solutions to the optimal allocation problem. And, solving this problem involves not only the intractable computational problem of optimization but also the more subtle problem of taking into account “unknown but possible worlds” variables. For example, before deciding on what to cook for dinner, I often browse the aisles at my grocery store to see if something is inspiring. The result is quite different from what would have happened if somebody delivered bunch of groceries to my door. Similarly, flawed studies like the famous ‘arsenic-life’ or say the 2022还能用的梯子 actually triggered all kinds of interesting science.
As ominously presaged by the title of their own blog article “Preregistration: A plan, not a prison“, creating a global plan without truly solving the allocation problem is highly likely to fall short of the heuristic free market solution and feel very much the prison to the players put in sub-optimal positions. Of course, when we add to this all the failures of human foibles, it might be good to remember how the well-intended revolutionaries soon moved to the absolutism of the Bolsheviks and the subsequent even more unfortunate autocratic events.
So, do we really want sanitized science delivered in a Harvest Box every month? For me, I really enjoy my occasional Big Mac and I’d rather take my chances with some fake p-values and irreproducible results.
[[Addendum]]
After I posted this, @BrianNosek kindly replied to my tweet and we had the following exchange:
So, I think it comes down to where each of us thinks the “right light-weight” line sits. If some one commits a bad act, clearly the society incurs a cost. We can take various actions to suppress the probability of the bad act, lowering the expected cost. But, every suppressive action has its own cost and we have to consider the sum cost. In general, simple punitive actions (e.g., censuring a researcher when they commit fraud) is less costly to execute compared to controlling everybody’s actions for prevention (think taking off your shoes at the airport). This is Foucault’s “punitive city” versus “coercive institution” dichotomy.
What action to take to minimize total cost depends on the cost of the bad act and the incremental suppression costs vis-a-vis the incremental reduction of the bad act. We could have situations like the left figure below or the right figure. In fact, sometimes the lowest cost might be to do nothing (e.g., children trespassing on grass). And, I admit some actions should be absolutely prevented despite enormous costs of suppression. The difficulty is we don’t know what the cost functions looks like for the issue of reproducibility in science. (Or, for that matter, we don’t seem to investigate cost functions for most rules we adopt or don’t adopt.) However, once put in place, coercive institutions tend to have an insidious tendency for viral spread and economic entrenchment of interests for maintaining the “political technology” of coercion. I think we are all pretty familiar with that.
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Motivated by Lior Pachter’s end of year blog post from 2014, I dusted off an old essay I wrote posted on my lab webpage (with a little editing)…
If I walk into a casino and find the person who has won the most money at Roulette that night, what does that tell me about the Roulette skills of that person? We all know that roulette is a game of pure chance. Given enough players, there will always be somebody who has been lucky and won a lot of money. One night’s winnings tell me nothing about the ability of that winner. In fact, we also know that if somebody wins night after night, that indicates something much more shady than Roulette skills.
Some games have less randomness, say poker, but nevertheless the results of any single night or a single tournament is not likely to signal the winner’s skills. Chance plays a major role in the outcomes of even seemingly high skill games. It is a well-established result that Wall Street fund managers’ year-to-year performance is uncorrelated and the overall pool of managers fails to do better than the overall market.
In one of his books, Malcolm Gladwell discusses examples of where it is difficult to assess somebody’s potential at some task, say a NFL quarterback, when they are measured for performance that is not related. According to the experts, the college football game is very different than the NFL game at the quarterback position. Thus, the best college quarterbacks seldom continue their success at the pro level. One might consider this just a problem of the correct measurement. So, it would seem a no-brainer that if we make the right measurement, e.g., previous success rate, then we should be able to predict true skills and future success probability. But, if a game has a high chance component–which is the case for most tasks in life, a person’s track record may not be so informative. The individual might have been lucky. And, given enough players there are always winners.
The problem is pronounced when considering extreme achievements in complex games. Any extreme achievement is a rare event and complex games makes the results more prone to chance fluctuations. We know coaching in NFL requires skills. But, does winning the Super Bowl foretell the ability of a coach to lead another team to the same rare achievement? The tricky thing is that there is always a Super Bowl winner; always somebody who made a killing in the stock market, etc. That is, there is always somebody in a large group that achieves extreme success; like the winners at Roulette.
The above thoughts came to me as I mused on the many extremely accomplished biomedical scientists I have met—those at the very top. What struck me the most was the degree to which many were narrow in view and single minded with a high level of self-conviction. These traits may come from the standard ego boost, to which all of us would be susceptible if we had similar levels of achievement. But, it also felt like there was more than that. There were perfectly nice, collegial, even modest, people who nevertheless had very dogmatic and narrow scientific views.
Biology is one of the youngest of sciences addressing highly complex and unpredictable phenomena. While important discoveries have been many, not too many of them could be described as having been predicted prior to the actual fortunate discovery. Nature is constantly surprising us (which is why the discipline is so delightful to some) and many of the previous knowledge is quickly overturned, either wholly or at least in details. And, one would be hard pressed to find Nobel Laureates who achieved high impact results more than once.
Given such variable history of progress, why is the field so conservative about accepting new possibilities? The answer I believe is that under such unpredictability, the successful strategy is to focus narrowly, ignore negative evidence, and then get lucky. Given ten thousand narrowly focused scientists and ten thousand broadly minded scientists, it is more likely that great success will come from the former rather than the latter. This is a basic result of portfolio theory for high variance games. Biology is a field for hedgehogs than foxes.
Three thoughts:
One. I once read a sports story that described the typical post-career trajectory of highly accomplished tennis players. Tennis is solitary sport with as many opportunities for errors as for winners during game play. An important trait for players at the top is the ability to immediately forget errors during play lest obsession on the mistake impedes the next point. The article suggested that such traits, while great for tennis, do not translate well into the next stage, leading many of them to repeatedly make mistakes in life’s decisions. Given a selection game, whether the game is science, sports, or finance, the traits that result in success can be surprising, unanticipated, and not translate well to seemingly related tasks.
Two. It is hard to believe that a Nobel laureate might not be the genius, deep thinking, and creative person we expect them to be. In some fields, that might be the case, in others a different trait might be selected. We have certainly stopped being surprised when we find that sport stars don’t turn out to be social role models. We should stop being surprised when the most successful fund manager from last year wasn’t the person with the deepest analysis of the market but rather a crazy risk taker. We also shouldn’t project Einstein into every highly accomplished scientist. A person’s record is important but just as important is the characteristics of the game in which they are successful; how much chance plays a role, and what traits are actually being selected.
Three. I do not mean for this to be a knock on successful biologists. I am confident that if biology were filled with deep creative thinkers, and only such people, it would make no progress. Given the complexity of the material, every observation would throw things into doubt, open new inquiries that abandon previous views, and generally cause endless meandering. It is highly likely that Biology requires an army of single-minded people whose work collectively results in great discoveries because a few chance upon important phenomena.
Biology from the point of view of portfolio management:
–What is good for the individual may not be good for the field.
–And, what is good about the field (depth, creativity, high-risk exploration) may not be the good (trait) of the individual.
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The Mold in Science’s Bathroom
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About once a month I notice the black smudge in the corner of my shower—it’s mold that I keep telling myself I need to take care of. But 29 other days, I don’t see it. If the same smudge was in a hotel bathroom, it would probably be the first thing I noticed. Familiarity drapes invisibility cloaks on our daily lives including the rot we immediately notice when step out of the familiar.
My life is usually happy and normal but as I travel around, every once in a while I have this sudden jolt of “stepping out”. How strange is it that in the 21st century, in one of the most advanced countries, we take it for granted that if you end up in prison there is a decent chance that you will be raped? To the extent that we have a common urban legend of “pound me in the a$$” prison. That is, somehow we’ve normalized the idea of violent prisons as part of the social contract.
What else? How about the normal expectation of absolutely shitty schools in urban or economically disadvantaged areas? Or, the recent events reemphasizing the banal normality of police brutality, guns in every fool’s hand, people without health care, and so on. I don’t mean we don’t recognize these things as problems, we do. And, some people dedicate their lives to solving these problems. But, for most of us, like the mold smudge in my bathroom, we are horrified when we see them, but we live our daily lives without seeing them. Instead of being intolerable social conditions, which they should be for any advanced country, they are part of some intractable tangle we accept as part of normal life. Twenty nine days of invisibility is okay with me.
Things that should be abnormal cancers to a decent society have somehow become, dirty, but normal part of life. One thing that especially stands out to me is the rather uniquely American acceptance of the soft corruption of the rich and powerful. Admittance of children of rich donors, legacies from pre-historic colonial times, and other “holistic” policies for fancy schools are accepted part of society. So are foundations for the powerful that are really collection agencies; and, the idea of a White House full of friends and family advisors (this isn’t just a Trump thing) is okay. I mention these because those three things were the “crimes” under which the previous Korean president was impeached. Of course, all of these corruptions exist in other societies, but what is unique here is that we don’t really even think of these kinds of things as smudges to be noticed once in a while. Oh, studying my faculty handbook for some other committee work, I found that our university president has the power to unilaterally appoint anybody as tenured faculty. Very nice.
Actually, to back off a bit, the soft corruption I mentioned is not necessarily a bad thing. While it might be immediately unfair, there are long-term societal benefits to having flexible subjective college admissions, even trading admissions for donations. Allowing a university president, or the country’s president, to exercise subjective judgment can allow more effective governance. But, there is one big caveat. Having a social contract that allows a large degree of subjective judgement requires having transparent processes and for each actor to act in good faith with ethical principles. We are now seeing, with great astonishment, what happens when at the very top, principles of ethics and morality breakdown in an open society. We need the Pope to be holy and all of us to follow suit or the mold will find its warm niche.
What mold are we unseeing in the open society of science? One thing especially stands out. When I’ve tried to talk my collaborators into submitting to bioRxiv, they are hesitant. Some people who do submit, leave out information. In fact, some people never give talks on unpublished data. Why?They, we, all fear,
somebody might steal the idea/data.
We all have stories about when that happened to us or to friends. Just the other day a junior faculty came to my office about being scooped and how they will never again give a talk with unpublished data. Okay, why is stealing other’s work a thing? Why is “pound me in the a$$” science community a normal state of life?
I admit “stealing ideas” is an amorphous thing. A lot of times we do it inadvertently–some vague idea we had didn’t really click until we heard it from somebody else. What is an idea compared to actual work, anyway? Also, we all have source-amnesia. Well, sexual harassment used to be an amorphous thing too. Maybe she/he kind of wanted it; it might have been consensual; what do you expect in Hollywood, etc, etc. Yes, it used be a corner smudge we chose to unsee most of the time, which we are finally beginning to point out for the malignancy it is. Something that seemed to be “locker room” shenanigans, when we step out of the familiar, is revealed for what it really is and we can educate ourselves to be vigilant. In the meanwhile, although we don’t feel so honor bound about other’s scientific work, strangely, we are extremely hygienic about plagiarism. That is, this idea from humanities that prose is sacred (because that is the creative output in that domain). Even the idea of self-plagiarism is a thing. You better reword that methods section for the method that you used for the 10th time. But, hey, if you saw somebody’s poster with a good idea and you decided to do the same thing, its all fair competition and whoever gets there first wins.
Of course, stealing ideas is not the only normalized corruption in our scientific lives. Deliberately leaving out attributions (yes, you know who you are), torpedoing a grant for competitive reasons, trading soft favors, threatening junior people in the field, withholding data and materials, on and on and on. One of my favorite gadgets: I publish a derivative work with proper citations first time, but then from the next set of papers only reference my derivative paper making this whole body of work mine. We know these are “bad” things but not so bad that we would think of them as bad as, gosh, plagiarizing.
Following norms of our greater society, the scientific society especially tolerates (unsees) corruption at the top, the privileged. Pretty much every one has stories of misbehavior by big-time scientists. I have my suite of stories, all the way from stealing grant funds to stealing authorship positions, to actual criminal behavior. But, we stay silent or sort of chuckle over the stories over beer–until somebody actually gets caught with hookers and drugs. The powerful get a pass. Recently, there was a hullabaloo over some alleged plagiarism (actually, idea copying) case by some Chinese authors of a paper by a Johns Hopkins professor. A whole bunch of people either resigned or threatened to resign from the board of Scientific Reports for their (mis) handling of the case. Of course, correcting misbehavior is a good thing. But, I couldn’t help think about whether the same people would have acted so forcefully if the accused were a chair at, say Penn. In fact, when possible misbehavior is called out, especially of powerful people, there is a lot of head shaking and accusing the accuser (sound familiar?) or let’s all be collegial calls.
We are finally moving past blinding ourselves to the Weinsteins of the world. Why are we not treating unethical behavior in science, the real unethical behavior–not the canned things we teach in Responsible Conduct of Research sessions, as we treat sexual harassment? Abominations antithetical to the open society of science? Despite Retraction Watch, scientific fraud is a far rarer problem than simple unethical social conduct of scientists. Or, maybe ethics is the wrong word, setting too high a goal. We all think we are ethical after all. Let me put it differently:
Why do we accept jerks and selfish assholes in science?
This isn’t just about being nice. Remember that because we think science is full of selfish assholes that will steal our ideas, sabotage our grants, and be vengeful with reviews, we act in ways that are not conducive to open conduct of science. Imagine a world where we know for sure nobody actively steals ideas and you just met somebody who is working on the same project as you. Cool! I can’t believe you had the same idea too. Let’s work on this together!
Every year, I know less of about teaching—and, know less, period.
I always give my students these slides, LearningtoLearn, from my wife Ingrid Olson on the cognitive science of learning.
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Don’t let the journals win
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Recently, two somewhat different topics on the business of science came across my Twitter feed.
The first was yet another push for “reproducibility in science” by 72 authors whose latest prescription was to set p = 0.005 (under Neyman-Pearson hypothesis testing) as the new threshold for “significance.” This paper was picked up by the usual Nature et al. press and, of course, generated lots of thumb-time. Without irony, an accompanying Center for Open Science blog post suggests:
“the fact that this paper is authored by statisticians and scientists from a range of disciplines—[…]—indicates that the proposal now has broad support.” (my italics)
That is, the fact that 72 self-selected individuals out of hundreds of thousands of researchers signed on indicates that the proposal has broad support.
Well, regardless, reproducible science, like apple pie, has to be a good thing (maybe). The paper is careful to point out that the proposal is not about publication standards or policy but standards of evidence in science. That is, it is about science.
So then, who in science needs this proscription on the use of the word “significance?” Suppose there is a risky and expensive experiment or maybe even a new dissertation project. I am trying to imagine a student arguing (against advice of caution)
“But, but, the article said it was significant!”
In fact, even for very well executed ground-breaking studies, typical journal clubs are exercises in skepticisms, take-downs, and “what-about-isms” (probably to the detriment of the discussants). Do grant review committees take at face value an applicant’s claims of “significant” preliminary results? Do hiring committees?
Q1: To whom is regulating the use of the term “significant” valuable?
I want to bring up the second topic before trying to answer the above question. This involved another (often repeated) discussion on whether one should cite papers in preprint servers like the new bioRxiv. Without regurgitating the various of pros and cons, much of the argument against citing a paper in a preprint server came down to “giving validation” to something that might not deserve such validation. That is, it was again supposed to be about standards of evidence in science. Science will benefit when we only acknowledge that which has been okayed by three people—including the notorious Reviewer 2.
Any human activity, regardless of whether it is art or science, acquires an economic structure. Efficient operation of the economy requires exchange tokens; we would rather not cart around bushels corn to exchange for milk so we make up credit papers (i.e., money). In science, the economy is supposed to be organized to enable exchange of ideas. But, we also need efficiency, so rather than read the candidates’ papers, we look up their h-index. Time saved. But, use of money or tokens like citations requires establishment of valuations (how much is that puppy in the window). So, one might think scientists who only want to cite “peer-reviewed” work are attempting to create accurate valuations—despite the Dutch Tulip prices created with drive-by-citations (see Lior Pachter’s discussion of this wonderful term from Andrew Perrin). But, what value is being assessed by citations as the valuation mechanism?
This brings me back to the above “significance” issue. Who cares about this language use? As I mentioned, I have never experienced anybody changing their negative opinion because some authors stated that their results were “significant”, statistically or otherwise, that is, if they actually read the paper. If indeed well-regulated use of the term significance leads to reproducible results in print, it should save people’s time. Well, but the original 72 authors of the p = 0.005 paper state that they are not talking about publication standards but language descriptors (valuations) and suggest adding other descriptors like “suggestive.”
But, hey, why even try to convert a metric scale (real-valued probabilities) into some vague ordinal scale? Because, the journals—more specifically the non-expert editors proliferating in current commercial journals, care. Significance is the bouncer behind the velvet rope they use to enshrine the (high impact factor) journal corpus. In fact, many of the journals explicitly ask the reviewers about “significance”. And, those polite rejection letters mentioning “more specialized journals” always mention “significance”. Yes, I know statistical significance is not the same thing as these uses of the word “significance”. Or, is it?
No one can argue against the idea that science demands everybody to do their due diligence. But, the specific concern has been focused on journal publications. Who made the printed words in peer-reviewed journals the matter of record? That is, when did putting scientific work to print become canonization instead a form of communication? And, who decided citations of such printed works should be a valuation token? I don’t know who decided all this but I do know who benefits (the answer to above Q1 and Q2): The Journals.
For the journals, there is a clear self-interest in establishing themselves as “all that is fit to print” and the “matter of record”. That is, nothing would make the journals happier than being the gate keepers of Truth. But, should this be also true for science and scientists? If we look at papers from 10, 20, 50 years ago, what percent of them hold up? Should Newton have been prevented from publishing Principia since he didn’t take gravitational curvature into account? Science is the never-ending search for, and refinement of, understandings of nature–which we pursue through exchange of ideas. We communicate these ideas to each other through the printed medium because it adds precision and distributional efficiency. We established the tradition of peer review because it helps increase (in some undefinable manner) the quality of the communications. Into this economy, commercial journals and journal empires came and, mirroring the rise of the financial sector in the real economy, established a derivative market where the number of publications, citations of publications, impact of publications, are made to replace the actual value of science itself. More they can convince us that “validated citations” are important and that only “significant” results get published in significant journals, more they solidify their position and substitute publication for science. They would like to see you bite down into Credit Default Swap papers of “Altimetrics” than an actual apple.
We are all human and to some extent efficiency and expediency makes us all admire a CV with a large list of Nature, Science, and their baby critter journals. But, we need to remember that the interests of these journals are not the same as the interests of science. Journals literally bank on our asking them to validate us.
Don’t let the journals dictate our values. Don’t let them win. Resist.
Addendum:A more serious question is what percent of published papers should be reproducible? If you think 100%, you have never thought about the problem of optimization over a rugged landscape. And, Nature is rugged indeed.
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About Me
Junhyong Kim–I am a Professor of Biology at Penn. I’ve spent 30+ years in biology doing various things but I am mostly interested in the “theoretical structure” of things.
This is a personal blog and all posts, opinions, and writings are mine and only mine with no associations to my employer or any other entities.