Peer-reviewed papers are getting increasingly boring

I largely agree, but we do not write all these papers "so tax payers can sleep". We write these papers because the administration incentivizes us to get the highest profile publications with the lowest effort possible. In relatively creative fields (i.e., much of computer science), this can even mean to make friends in the community and co-author papers with them without being the one who does any of the hard work. (In other sciences, it means being the one who pulls in the money, as far as I understand.)

A related problem I see is that we treat all papers the same: position (opinion) papers, reviews & surveys, and "hard" results (relevant proofs, strong empirical results, software artifacts that are deployed at scale in practice etc.). As the blog post somewhat suggests, the administration should primarily ask us to summarize these results when assessing whether we are worthy of funding and faculty positions; sure, it takes more effort, but I think it is possible.

Or even more reductionist there are only a finite amount of talented and smart people ever in history doing truely new and interesting stuff.

It’s just the nature of the game. You can’t just turn a dial and add more talent.

Although a bit off topic there are some authoritarian nation states who tried to do this by social engineering. Soviet Union made being an engineer a common place job title and China is trying to make tons of super smart kids at STEM. But we all know there is more to being smart than forcing kids to go down certain academic route and get top end scores (you know the whole creative side and capacity for original works to be created).

The democratic approach still seems to be the winner (not just due to brain). It’s as I mention always going to be a small minority who do great things. That doesn’t scale up artificially.

Are papers getting more boring or does the reader just find less novels things to read as they read more and more? Maybe the reader is bored of the field in general. The 500th time you do anything isn’t as exciting as the 5th time.

On another note, why does everything have to be exciting? Small incremental improvements over the years is what I aim for.

I think I agree with a large chunk of this: there are inevitably triage/discovery problems as the number of things/options go up.

The cost of evaluating each remains fairly constant, and at some point production outstrips the ability of even extremely-interested/dedicated individuals to have a good handle on it all. Beyond this point, you either need organized collective effort (and trust) to efficiently distribute the work of keeping up (and synthesize the results) or the larger community will be wasting ever-increasing slices of potential energy to extract increasingly less knowledge of the scope of activity.

But there's a difference between simple volume growth for good reasons (i.e., people chasing incentives that are aligned at multiple levels of society), and volume growth caused by people chasing incentives that are misaligned at one or more points up the stack.

If the researchers are spending their time on things even they find boring because Goodhart's law, I think it is important to recognize it and try to undo the misaligned incentives. They're not only externalizing a cost on their entire field of knowledge--but we're also collectively suffering some ill-defined opportunity cost of whatever it was they would've spent their time on if they were following curiosity.

This is a bit off-topic to papers, but perhaps there's an angle.

One answer to all these propositions is that the valuable stuff is still there, you just have an additional flood of mediocre boring predictable stuff.

I don't think this is true for most things with a mass market. I think products which have efficiencies of scale - or low marginal costs of reproduction - suck up more capital, which raises certain basic levels of standards and polish and marketing, but also greatly increases capital risk and thus reduces investor risk appetite for product novelty. These mass market products starve the mid-market of attention, which makes the mid-market less capital efficient, which means the mid-market needs to get cheaper and cheaper, lose polish, until it's less attractive to the mass market of consumers, and so on in a spiral until a certain spartan rawness becomes its own aesthetic - indie games, indie films, indie music.

I think there's a concrete example which demonstrates the actual absence of that long tail of interesting content, and not just that it's harder to find: blogs.

Blogs were great in the mid 2000s. The market did two things: it matured - the best blogs got more mindshare and turned into something closer to media organizations, much more capital intensive with full time paid writers, while and Facebook and Twitter sucked up the mass market of newsfeed consumers, both on the producer and consumer side, making it easier to produce low-value inanities and easier to consume tidbits from celebrities. This sucked the air of attention from blogs; being long-form, they were too hard to write and too long to read; and being unpaid, they didn't have slick editors or snazzy design. So a lot of them shrivelled up. There are still niche blogs, plenty of them, but a lot fewer - and we can track this loss, because we have (or had) them in our newsreaders.

"Science advances one funeral at a time"

-- paraphrased from Max Planck

Inevitable of not, this has real costs, in that that government will eventually turn off the gravy train and the "good" and "bad" research alike will be negatively impacted.

In other words, academia is sowing the seeds of its own demise, and with it, the official institutional pinnacle of our culture [please don't wince too hard when reading that!].

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The solution i think is less research but more library work. See https://blog.khinsen.net/posts/2020/07/08/the-landscapes-of-... and https://hapgood.us/2015/10/17/the-garden-and-the-stream-a-te... which it cites.

The amount of work library work we are not doing is just staggering. Consider these claims:

- There should be an accredited-author-ornly "kernel wikipedia" which the main one can choose to incorporate, almost like release vs staging branches.

- Different subfield way wish to keep their own intentionally biased corpuses, like https://ncatlab.org/nlab/

- After 6 months, virtually no one should have to read the original research article, because the librarian core will have incorporated it's results claims (however controversial) into the appropriate articles

- Textbooks / "knowledge bootstrap plans" should be continuously updated from the encyclopedia, not unlike how bootstrapping is managed in a package repo

- Librarians do the work, but also adjudicate disputes, as researchers will be naturally incentivized to contest how their work is incorporated as that is the primary way it is consumed.

Music is becoming more generic because musicians can rapidly reach a wide audience and iterate quickly, so they see what works and what doesn't and continue down the path of sound that produces the most money.

> One answer to all these propositions is that the valuable stuff is still there

I don't understand the popularity of this argument. Whilst someone might (theoretically) have written the Great American Novel in his or her basement unbeknownst to pretty much anyone, a lot of art is fairly resource intensive and thus you can say with extremely high confidence that's its not being produced and the fault lies not with people not looking hard enough. Same with research and journalism.

>It's an illusion to expect that every researcher can pump out multiple really interesting non-boring papers every year. So we pretend. We write, we cite, we present, overiflate, overpromise etc. It must look like there is steady hard noble work and toil. It's like a ritual. The scientists are writing all these papers so tax payers can sleep well that their money is paid for hard work.

The flip-side to this is that there is a glut of moderately motivated scientists and PhD candidates. As a result, the demand for conferences and citations is self-sustaining to meet the expectations of millions of people wanting to enter the academic world without a clear plan beyond joining the world itself.

It's as though the English-major-to-professor cycle has also become a reality in the hard sciences.

> So we pretend. We write, we cite, we present, overiflate, overpromise etc.

> so tax payers can sleep well that their money is paid for hard work.

It's a bit contradictory.

I won't go into scandalized rant because it's useless, and there's no point shouting against the universe from a bedroom chair. Still it's a bit disheartening. I wish the scientific world could reinvigorate and pump some spark back into the field.

Rick Beato rails against gridding and autotune in music over on YouTube.

My wife, a health outcomes researcher, points out that the expectation is that every little publishable bit be kicked out the door for a pharma project.

Historically, they would have dropped a single summary result at the end of the effort.

Now, she's trying to "autotune" the neutral or even negative results. Nominally in the name of "transparency".

If this is true, the need is a research Adele to come along and shame the riff-raff with sheer natural brilliance.

The problem isn’t the existence of the papers, it’s the years of effort that go into producing the papers.

It’s the failure to harness the hard work and brainpower of so many brilliant people towards efforts that would meaningfully improve the lives of others.

In the line of your comment about tax payers money: one of the biggest issues IMHO is the disfunctional "market" here because most of the work is paid easily by the tax payer . Particularly publishers are mostly not paying for reviews but are paid for journal and conferences largely on quantity (with few noble exceptions). The effect for a long time now was an ever increasing number of conferences (peer reviewed proceedings still make a large share in CS) and journals. What is actually worse IMHO, the review request get more and more and are largely boring. So you really have to attract the attention of the reviewer to not trigger the reflex of looking for reasons to reject (or worse the opposite, which may account to the same because there are always other reviewers, so its a matter of luck who gets assigned)

I think better structures are needed that actually incentivise good reviews. This would lead to better papers, too. There are multiple options for this. Maybe it is simply time to see reviews as publications themselves and say goodbye to flawed blinded review process. Another thing would be to take the publishers out of the game. Even IEEE and ACM have become largely a playing field for power politics between the US, China and Europe . I think we could do better and be more inclusive here. Publishing reviews and rejected work would further make meta studies much more reliable removing also bias towards positive results (who actually wants to hear about easily replicatable negative results at a conference)

All what you say is true and I appreciate your deep thoughts.

There is another dimension to that though. It's the long tail. The internet has tremendously facilitated mixing existing content. That's creative too but not in the original sense of creating something new.

With detached knowledge before the internet age much less content has been produced and I would assume the novelty to mixed content ratio was very much in favour of new content instead of mixed content.

Internet technology brought us search engines but their search algorithmus favour those paying most instead of providing a service to discriminated remixed content from new content.

Katalin Karikó, the Hungarian scientist that pioneered the mRNA research, was academically demoted at UPenn because the university considered her research as "impractical" and "waste of time" [0]. That was in 1995.

In 2021, she is a hot candidate for the Nobel Prize for the very same work, which led to mRNA vaccines.

[0] https://www.wired.co.uk/article/mrna-coronavirus-vaccine-pfi...

Isn't it a sign of system failure when a researcher has to beg and plead to get his results published and no one is interested in his publication until someone who understands the break through happens to stumble across it?

Boring is often a good thing, not just in science. There's a reason that "May you live in interesting times" is considered a curse.

Think about the year we just had. Whatever else you might say about it, it wasn't boring.

[Clarification] Individual local experiences may have been boring at times, but the year as a whole, from a historical point of view, was not. And the things that made it non-boring also made it suck big fat honking weenies. IMHO of course, but I'm pretty sure most people on earth would agree with that assessment.

I think we need to take Vox documentaries with a grain of salt. They’re not as thorough as the Economist, etc. and have their own agenda mixed with YouTube content engagement metrics. You can argue that’s the case with any publication but IMO YouTube forces content makers to do crazy shit like exciting facial expressions in thumbnails for better engagement.

You make a good point.

This sounds like the age-old balance between maintenance/repair and breaking-new-ground/innovation. My personal sense is that there is and always has been a gendered dimension to striking this balance, and varying levels of predisposition that bellcurve along gender-specific neurotypes.

For me, once I was pointed to this axis, I started recognizing it everywhere -- legal institutions, the way companies are run, etc etc

Hofstede's cultural dimension studies commissioned by IBM in the 50s (?) have things to say about this too

Yes, boring in the conventional sense is desirable from a scientific point of view (because the preference for surprising results leads to the biggest problem science has today: most published findings are incorrect). The linked article doesn't really do a very good job of explaining what "boring" means to the author, but my hope is he doesn't have a problem with boring in the sense of negative findings or unsurprising results.

Percentage ownership of resultant intellectual property.

A good example is the Minneola, a wonderful citrus fruit. The plant patent is owned by three parties: the University of Minnesota and the two inventors.

i would say to emphasize bibliometrics measures of productivity less (how much you publish) and emphasize measures of social impact more. But it easy to say...

The elephant in the room, IMO, is that there is only so much ground to be broken. The physical world is fundamentally limited and limiting. There's a limit to how much there is to know about it, and as we come to know more of the big things, it becomes more and more difficult to learn the smaller and smaller things. This outcome -- that the rate of groundbreaking research is slowing -- is what we should expect, even under a consistent policy.

I left academia for industry, so my opinion might be colored by the transition.

The way I see it, the easy problems that can be solved by one or two individuals are mostly gone. You need large diverse teams to tackle interesting problems.

To translate this into policy, you need opportunities for many more first authors, and you need to try to incentivize completely different departments to work together.

This is something Patrick Collison (Stripe CEO) has been talking about these past few years. Here’s an Atlantic article from Collison and Tyler Cowen called “We Need a New Science of Progress”

https://www.theatlantic.com/science/archive/2019/07/we-need-...

And an EconTalk episode on the same subject (which goes into more detail than the article)

https://www.econtalk.org/patrick-collison-on-innovation-and-...

Not sure if it applies to other fields, but as I observe in CS, many professors start tackling more interesting & risky projects after getting their tenure. Even though their students/postdocs still value paper count a lot, they care more about producing ground breaking works.

Many novel funding approaches have been proposed in an attempt to free scientists from the endless grant-> public-> grant cycle.

One is to accept only mini grant proposals, say 10 pages at most, and screen these to meet some minimum threshold, say, aiming for the top 20th percentile. Then a random subset of these get funded. This helps diversify the funding somewhat, and hopefully catch more "risky, but interesting" projects.

Another approach has been universal funding. The most basic is "everyone gets X research dollars", and any additional funding would require submitting grants on top of that. More complex schemes propose "everyone gets 2X dollars, but they must donate X to other researchers", which allows some people to accumulate the funds necessary to conduct big, expensive work. But all of these proposals aim to minimize grant writing and review, and hopefully to diversify the kinds of work being done.

Longer windows of evaluation could also be useful. Big interesting ideas take time to develop and support, but the competitive academic environment demands quick evaluations, which make ot difficult to sustain long projects. Evaluating a research project after 5 years, instead of 1 or 2, could help alleviate some of the pressure on researchers so they can pursue longer agendas.

Every researcher can come up with their pet theory and solution. Ultimately, I think that all of these approaches, and many others, have merit. But we need to experiment with different policies to see what works.

I think the problem is requiring excessive polish in academic papers.

This causes two problems:

1) It's easier to polish something which is incremental.

2) It's easier to achieve the look of polish by purposefully hiding issues and smoothing over edges.

I'd personally like every paper about a technique or algorithm to include as many problems where it does terribly as where it does well -- this is annoyingly uncommon. Also, people shouldn't be afraid to discuss all the nasty unfinished bits but in practice if you mention them reviews say "well, go fix that before acceptance".

In my limited experience as a disillusioned PhD student dropout, the issues are in approximate order:

1. Publications in prestigious journals have become a measure, not a way to communicate. This leads to perverse behavior.

Any kind of project that would involve deep work is very scary, unless it has early low-hanging fruit called easy publishable papers as intermediate steps that are easily published. I personally felt I was encouraged to find such fruits without too much coherence in what I was doing. Preferentially one does not have to learn or study anything challenging, because that makes the fruit potentially much more difficult to pick.

My proposed solution: do not judge researchers by length of their publication list to evaluate them to hire/fund. Judge them by a selection of their recent work instead and maybe their presentation what they are doing now.

2. This is connected to another problem, corrective feedback comes quite late into play, when the most work has been done and it is very costly to change anything. I feel better results could be had of reviewers entered the stage when study was being drafted.

Currently, submit a manuscript into a journal, get it rejected after a round of substantive, critical but correct reviewer comments? Optimal thing is not to review the work as suggested in the light of new ideas, but try to find a less prestigious journal likely to accept it with minimal work.

3. This has effects on conferences. While their primary purpose has always been presenting ones research and hearing about others, they kind of turn too much into a platform for advertising your research so that you get cited. Thus the general feeling can be quite one-way, and there is less knowledge enhancing communication by scientific discussion. Some conferences are better than others (amount genuine curiosity and interest helps), but sometimes I felt people would come to deliver their own little advert, maybe as chore between meeting their personal friends, instead of coming to talk, both receive and offer meaningful updates.

4. PI-centered networks and death of university department. I believe originally university departments were formed because it was thought beneficial and reasonable to have scholars with similar interests nearby. Social networks are probably quite important part of science, and is easier with people who are located often in the same building. Research group culture is a fascinating way to have groups of people nearby who don't communicate. It appears that to PI, each unsanctioned contact from their underlings to outside the group is a distraction at best (if it leads to underling working on publishing something PI is not involved in) or an unwelcome threat at worst, because it risks changing their plans, whether they concern the projects underlings should working on, the author order on planned manuscripts, or something else. All presentations to group outsiders is about signalling importance, prestige and coolness, but no research communication within department to help with unfinished work.

Solution would involve stopping funding faux institutions within institutions, and start paying researchers in a way that encourages them actually collaborate within their physical departments when it is useful. (Salary paid by university/dept., no project grants.)

5. I suppose science moving very large projects involving lots of contributors can not be helped, but it is incompatible with publication authorship as the currency of value in academia. It leads to authorship beimg traded as a currency within projects. One is "paid" by official authorship in some papers; sometimes a person can show their magnanimity by bestowing it upon some people who participated. Sometimes technical or statistical help does not get acknowledged.

IDK what to do about that. Moving out of evaluating publication lists to evaluating personal contribution/capability might help. In addition to big publications that are meant to communicate the big findings publicly but leave outsiders to interpret author order like tea leaves, record publicly some documentation what exactly each individual did, in their own writing, and that documentation is what the contributors should refer to in their CVs?

A related point is that we could improve how good work is bubbled up. Another poster pointed out Allison’s work that led to the Nobel prize, and he claimed it was appreciated by just one group and that helped it get broader notice. How many great works go unnoticed now just because there is no famous author on the paper who has the bully pulpit to command attention?

I think it might be a mistake to frame the issue as scientists not doing enough groundbreaking research. Those scientists do exist in greater numbers than before and have the right incentives guiding them. What is happening instead is that the superfluous group is expanding at an ever greater rate.

These are two parallel worlds being discussed as if they were one.

To answer your question, I believe we need to look outside of academia to relieve the pressures on most people so that fewer are tempted to add to the science glut. I'd venture to mention UBI but that's a whole can of worms

Give people tenure after their PhD and pay them a crappy salary that is guaranteed for the rest of their lives.

The only alternatives I see:

1. National research funding agencies and universities need to stop doing their assessments based on publication counting. Of course, publications need to be taken into account somehow, but at the very least these indicators should be weighed by curated rankings of journals.

2. Existing publications can be used as an indicator for how much output is to be expected in the future, but the goals for research output should be kept reasonably low. You cannot control the output of researchers, you can only control which ones you hire and (to some extent) the type of research they conduct.

3. Hiring in academia needs to be based more often on screening candidates by committees of outside experts in the field instead of local staff and people who don't know the area well. Projects also always need to be evaluated by experts on project's topic. (As strange as this may sound, this is often not the case!) It might even help to prune away irrelevant indicators, e.g. ask candidates to submit only 3-5 of their best publications and completely ignore the rest. And by "completely" I really mean completely. The reason is that if you have two researchers and one of them has 20 publications with five really good ones, and the other has 40 mediocre publications and not a single good one, then it is very hard for a normal assessment committee to justify taking the first one, but it's always easy to converge on the second one, even if that is exactly the wrong choice.

4. Assessment committees need to be told to evaluate the quality and originality of the research only. If you really want or need a certain output quantity, then make it part of the formal hiring criteria, not part of the scientific evaluation.

5. Increase funding for risky projects and risky individual grants, elimination of criteria that exclude unusual CVs (e.g. allow long time after PhD, people from other areas, people with time spent in business, unusual research suggestions). Originality should be one of the highest ranking criteria. There should also be a focus on versatility and hard skills. Even in the humanities, never hire anyone who says anything disparaging about mathematical methods and statistics, and never leverage people who don't know the tools of their trade into positions of power.

Basically, you cannot push scientists to anything. Once someone is hired at the postdoc level, you cannot steer much, micromanagement and constant evaluation are highly counter-productive. You need to hire scientists that do interesting research. Treat them like an investment in a startup: Most of them will fail but some of them will succeed. Give them a second chance, maybe even a third one, but not indefinitely many. The hiring policies and processes at universities are often bad. Candidates are not evaluated by experts, there is plenty of favoritism, boring high producers are favored over interesting researchers who want to built something up, because the local staff doesn't like scientists who "shake things up", and so on. There is a lot of inertia to overcome in Academia, being a good scientist can sometimes even be harmful to your career. Funding agencies need to steer against this.

Edit: Much of what I mention can also be achieved by getting an absolute top researcher in an area, give him or her an institute or research unit and ton of money, and let them do their thing. They know what to do and whom to hire. But it's expensive.

Honestly: more research $'s from government instead of industry. Industry wants conservative investments that reliably pay off.

I reject the notion that a dominant proportion of research publications are mediocre. Instead, the problems have gotten harder. Harder research questions forces careful, yet incremental, research programs.

I'm not sure that's actually something we want within the institution. IMO the most important thing is improving the overall _reliability_ of research.

On this note, and admittedly a bit of a (relevant) plug: I work at a startup called scite that's trying to improve this -- https://scite.ai

Citations are the primary mechanism by which scientific papers "talk" to one another, and one of the systemic issues we see in the status quo is a sort of numerical reductionism where a lot of emphasis is placed on "how many times someone is cited" without any indication of whether those citation counts are from papers that support or dispute someone's findings.

One of the things we do at scite is let you see, for a paper, how it has been cited (i.e. not just a count, but the surrounding textual context around the citation, and a classification from our model as to whether the citing work provides supporting or disputing evidence for the cited paper, or just mentions it).

That information is also aggregated to the author level, or journal, and so on.

The hope is that by providing (and improving) this service so that researchers can see how papers are cited, we're able to promote more reliable science (in addition to letting someone explore new subject areas / doing lit reviews much faster, and other things).

I just wanted to share that because a lot of the other comments were more abstract and it might help to include something more tangible that's being actively worked on now. There's a lot of interesting work in general in this space.

If you have any thoughts / feedback / questions, feel free to reply here (I check occassionally) or write to me at the email in my profile.

Only speaking for the US, but

Federal grant funding needs to be increased.

Indirect funds need to be eliminated.

The funding structures need to be reorganized. Some ideas I think have merit are basing grant award on a lottery system, or funding individual researchers based on previous research for a limited nonrenewable period of time.

Grant review panels need to be mixed up dramatically. Currently they consist largely of people who have received grants in the past. One of the biggest predictors of proposal rating is being a co-author of people on the grant panel. I think grant panels need to be based on some lottery system too, like everyone with an ORCID ID gets thrown into a pool somehow, like jury duty.

Universities need to be funded in a way that's separated from grant receipts.

Yes. And when “it’s just a job” people dominate it sets the culture, and makes Einstein’s life very difficult / improbable.

Congrats! What is your research about? What drew you to this field, and why do you think it’s important?

Congraturations on paper acceptance, but joy is very optional in research. Joy is emotional and it clobbers logical insight. Peer review is an attempt to guarantee a steady firm progress. It is a matter of taste --- do you want progress or just want to be comfortable? If you want joy, better to be a SF writer... Still, strong results with good execution are allowed to enjoy some freedom.

TBH, big ideas should not be in a paper, unless you can really prove it. I've read too many papers with grand new theories that hinged on an experiment testing the tiniest of tiny facets. All of these have been forgotten now, even by their creators.

Once you have enough experience, know the field inside out, and have gotten a bit of a name, you can write a book or edit a special edition of a journal in which you may set out your ideas.

The style of academic papers is intended to encourage objectivity I think. All the same I would agree it can indeed obfuscate at times and a more informal style could be both more enjoyable and easier to read.

So, Wikipedia, except with some sort of syntactical structure that allowed for formal evaluation and analysis of arguments...we could call it a "compiler" for "compiling" sets of rules, or "libraries"

This is an interesting idea and would work for something like Math or maybe theoretical physics, but once you get to messier fields like Biology it would be mired in hopeless confusion. Every experiment has so many varied parameters and restrictions due to things like ethics committees that standardizing it is nigh impossible. This is not even going down to fields like psychology.

I read a good study that suggested that so much time and effort (and hence money) is wasted on writing proposals for non-funded grants we should just assign a sizable fraction of the money by lottery instead, without needing lengthy proposals. Everyone knows you use the money for other stuff not specific to the grant regardless. The opportunity cost of writing all the rejected proposals would be saved and could be spent on actual science, even if some of it isn't top notch that otherwise would have been funded (and thats assuming that the grant proposal system actually selects the stuff mostly likely to be ground breaking).

I believe this is close to the truth. Moving one step further upstream, the emphasis on high ROI stems from an overall lack of availability of funding. Since there isn't enough money to go around, it becomes necessary to choose some more selective metric to pare down the pool of grant applicants.

There is a lot of caution in research funding. Some research is considered "safe", whereas others risky. IN a properly balanced portfolio, perhaps 80% of funding should go to safe work and the remaining 20% to more risky, but potentially high-reward studies. However this isn't how funding agencies usually operate.

At least in the context of the U.S. government, funding agencies are terrified of being seen as "wasting" funding, because that is a sure way to have funding cut by congress. The "Golden Fleece" awards, a congressman's attack on perceived frivolous spending, have routinely been targeted at specific research funded by the NSF and have helped make the agency afraid of being attacked by congress.

Most people do actually judge by citations rather than raw pubs. It's an open secret that you can shove out papers (acceptance to any venue, regardless of the quality of the work is probabilistic) with enough effort. Getting cites is harder (other than self-cites which is a seperate issue).

When I look up a researcher first thing I look at is their number of citations and H-10 index, then I look through their top papers (the ones that have been cited a lot). As far as I know hiring committees also care about these things.

Of course it isn't the only thing that matters, or the most important, but its much more useful than raw number of papers published.

This is whats done in science evaluation—the H-index for instance is built from a combination of publication and citation counts. Similarly, journal prestige is quantified using the Journal Impact Factor, which aggregates the average number of citation a paper in the journal receives.

As you speculate, these can also be gamed. Authors will cite themselves more to inflate their citations, or form citation carters with other authors to cite each other's work. Similarly, journals have been known to coerce authors to cite other works in the venue, in order to inflate their impact factor. Beyond these, there are issues with comparing citations across disciplines, article type, and other contexts.

> Eventually, pubs are going to start rejecting valid papers for being too incremental.

Many of hte most prestigious journals, such as Science, Nature, and Cell, already do this. However newer Mega-journals, like PLoS, have had explicitly the opposite policy, and state that they accept anything that is "sound science", no matter the size of its contribution; they have however become more selective over time.

I wouldn't call this validation. I think it's being discussed positively because it articulates what many of us feel to be true: peer-review is a broken mess. Same thing about bullshit jobs.

My doctoral degree has required training in both Computer Science and Social Science, and regularly interact with both communities. Drawing on this, I feel that this comment is unnecessarily partisan and divisive.

> 2) Mentioning the replication crisis in social science gets a lot of the social science academics observably upset and defensive.

The replication crisis is widely discussed in social sciences. Nearly every major social science journal will have at least one, likely many, editorials and articles on the crisis tailored to their field. Maybe this is explicitely a Management Studies thing? The field is relatively small and insular, and so cannot be generalized to wider social science. And are your experiences drawon from the community as a whole, or the faculty in your department?

> 3) I have enjoyed my time spent with CS academics a lot more, luckily have some interaction even now - the ones I have spoken to seem to lack the ego-driven blind spots the social scientists exhibit. The CS group seems to have a lot more fun with their research.

Maybe this is just the local community of wherever you studied? I've met equal parts ego-driven and chill people in both CS and Social Science. A major concept in most social science fields is sampling—I'd urge you to consider how representative the people you are talking to actually are, and how your sample might be biased from the global population. My prior is that there would be little difference in personality, in aggregate, between the fields.

> I.e. I have observed that even when a manager or leader wants to hire developers, social science damaged managers and HR will actively sabotage these efforts because they are still, fundamentally, driven by Taylorist, control fetish concepts (which they refuse to accept)

I mean, that's one possibility. The other is that hiring people is difficult and expensive, and that credentials are a quick and useful, if flawed, method of sorting through the pile.

And are most HR people really trained in Management? I honestly don't know, but I doubt that the typical Psychology or Sociology major, for instance, is going to know of, remember, or consider using Taylorist management theory.

It definitely seems that you enjoyed your time in CS more than your time in Management. That's great! CS is an important field with lots of cool people. But generalizing this preference into a wider philosophy that privileges CS at the expense of (all?) social sciences is silly.

Attitudes towards the replication crisis seem to me to vary between researchers in any given social science discipline. Those (careless?) empirical researchers whose careers are being retrospectively ripped apart are inevitably horrified (and coming up with a huge range of arguments both reasonable and unreasonable as to why they shouldn't) while theorists are mostly happy and younger empiricists are taking up the reproducability/better science challenge with some enthusiasm. Likewise, attitudes to perfect citation vary wildly. I don't care as long as it's vaguely consistent, which is a common (but not universal) position in my sub-discipline.

I'm not sure how much of your experiences are specifically a feature of management research rather than the social sciences in general. I spent a bit of time studying management (and being a manager, in pre-academic times), though now I'm a computational political communication academic. Management research is seen by the rest of us as a bit weird - a bit of an outsider discipline, with different attitudes and surprisingly little scholarly overlap. I wouldn't expect that many political scientists or sociologists to be Taylorists, for example.

Publish or perish, boring papers, and problematic academic management on the other hand - that is very familiar.