Tag Archives: Project

Intellectual Prestige Futures

As there’s been an uptick of interest in prediction markets lately, in the next few posts I will give updated versions of some of my favorite prediction market project proposals. I don’t own these ideas, and I’d be happy for anyone to pursue any of them, with or without my help. And as my first reason to consider prediction markets was to reform academia, let’s start with that.

Back in 2014, I restated my prior proposals that research patrons subsidize markets, either on relatively specific results likely to be clearly resolved, such as the mass of the electron neutrino, or on simple abstract statements to be judged by a distant future consensus, conditional on such a consensus existing. Combinatorial markets connecting abstract questions to more specific ones could transfer their subsidizes to those the latter topics.

However, I fear that this concept tries too hard to achieve what academics and their customers say they want, intellectual progress, relative to what they more really want, namely affiliation with credentialed impressiveness. This other priority better explains the usual behaviors of academics and their main customers, namely students, journalists, and patrons. (For example, it was a bad sign when few journals showed interest in using prediction market estimates of which of their submissions were likely to replicate.) So while I still think the above proposal could work, if patrons cared enough, let me now offer a design better oriented to what everyone cares more about.

I’d say what academics and their customers want more is a way to say which academics are “good”. Today, we mostly use recent indicators of endorsement by other academics, such as publications, institutional affiliations, research funding, speaking invitations, etc. But we claim, usually sincerely, to be seeking indicators of long term useful intellectual impact. That is, we want to associate with the intellectuals about whom we have high and trustworthy shared estimates of the difference that their work will make in the long run toward valuable intellectual progress.

A simple way to do this would be to create markets in assets on individuals, where each asset pays as a function of a retrospective evaluation of that individual, an evaluation made in the distant future via detailed historical analysis. By subsidizing market makers who trade in such assets, we could today have trustworthy estimates to use when deciding which individuals among us we should consider for institutional affiliations, funding, speaking invitations, etc. (It should be easy for trade on assets that merge many individuals with particular features, such as Ph.Ds from a particular school.)

Once we had a shared perception that these are in fact our best available estimates, academics would prefer them over less reliable estimates such as publications, funding, etc. As the value of an individual’s work is probably non-linear in their rank, it might make sense to have people trade assets which pay as a related non-linear function of their rank. This could properly favor someone with a low median rank but high variance in that rank over someone else with a higher median but lower variance.

Why wait to evaluate? Yes, distant future evaluators would know our world less well. But they would know much better which lines of thought ended up being fruitful in a long run, and they’d have more advanced tech to help them study intellectual connections and lineages. Furthermore, compound interest would give us access to a lot more of their time. For example, at the 7% post-inflation average return of the S&P500 1871-2021, one dollar becomes one million dollars in 204 years. (At least if the taxman stays aside.)

Furthermore, such distant evaluations might only be done on a random fraction, say one percent, of individuals, with market estimates being conditional on such a future evaluation being made. And as it is likely cheaper to evaluate people who worked on related topics, it would make sense to randomly pick large sets of related individuals to evaluate together.

Okay, but having ample resources to support evaluations by future historians isn’t enough; we also need to get clear on the evaluation criteria they are to apply. First, we might just ask them to sort a sample of intellectuals relative to each other, instead of trying to judge their overall quality on some absolute scale. Second, we might ask them to focus on an individual’s contributions to helping the world figure out what is true on important topics; being influential but pushing in the wrong directions might count against them. Third, to correct for problems caused by scholars who play organizational politics, I’d rather ask future historians to rate how influential an individual should have been, if others had been a bit more fair in choosing to whom to listen.

The proposal I’ve sketched so far is relatively simple, but I fear it looks too stark; forcing academics to admit more than they’d like that the main thing they care about is their relative ranking. Thus we might prefer to pay a mild complexity cost to focus instead on having future historians rate particular works by intellectuals, such as their journal articles or books. We could ask future historians to rate such works in such a way that the total value of each intellectual was reasonably approximated by the sum of the values of each of their work’s.

Under this system, intellectuals could more comfortably focus on arguing about the the total future impact of each work. Derivatives could be created to predict the total value of all the works by an individual, to use when choosing between individuals. But everyone could claim that is just a side issue, not their main focus.

To pursue this project concept, a good first step would be to fund teams of historians to try to rank the works of intellectuals from several centuries ago. Compare the results of different historian teams assigned to the same task, and have teams seek evaluation methods that can be both reliable and also get at the key questions of actual (or counterfactual) impact on the progress that matters. Then figure out which kinds of historians are best suited to applying such methods, and which funding methods best induce them to do such work in a cost-effective manner.

With such methods in hand, we could with more confidence set up markets to forecast the impact of particular current intellectuals and their works. We’d probably want to start with particular academic fields, and then use success there to persuade other fields to follow their example. This seems easier the higher the prestige of the initial academic fields, and the more open are they all to using new methods.

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Make Law Like Couches, Not Cars

Action movies often show fights in complex environments like factories, ships, kitchens, warehouses, or construction sites. In such cases, whomever knows more details of that environment can have big advantages in the fight. However, when people instead try to arrange a “fair fight”, they usually choose simple environments that combatants can know similarly well, like an empty flat walled square or circle.

Lawyers often fill their offices with big shelves full of law books. As if to say “Law is a vast complex machine you wouldn’t want to mess with without access to an engineer like me who knows all its details.” Or more relevant, “The arena of law is as complex a place for a fight as is a factory or kitchen. You don’t want to fight there without a warrior like me who knows all those complex details.”

However, the essence of law is for a judge to hear A complain about B, and then to issue a ruling to reward or punish A or B. And the main point of such law is to induce better behavior via shared expectations of such rulings. For that purpose, what matters about the law is those shared prior expectations; further legal detail beyond that has little social value.

Actually, added legal complexity and detail can hurt, by tempting people to learn more legal details in order to gain strategic advantages. Just as warriors fighting in a kitchen would need to learn kitchen details, people with possible legal conflicts can need to learn about arbitrary legal details, or to hire lawyers who learn them, even if those details do little to help guide prior actions by A or B.

Imagine that two people will hold a verbal debate in some physical space. Law without needless details is like the debaters sitting on a simple couch to do their debate. Such a couch has little other structure besides that which is needed to coordinate their locations and orientations. Which is good.

Now imagine a couch with lots of little pockets holding weapons or controls to make the couch poke people, change shape, get hot, or make noises. Something like a car. If you were to be in a debate on such a complex couch, you’d want to invest in learning those details. For example, you might be able to poke your opponent out of view at just the right moment. Even though that is a social waste.

Is a minimal couch-like law possible? Consider juries. Imagine there is little formal law, so that juries can rule most any way they choose. In this case legal expectations are just expectations over jury rulings. So if A and B know the community from which jurors are chosen well enough, then they know that they have shared legal expectations. And they know that there’s not much either of them can do to gain more info on that. Their law is a couch, not a car.

Of course it is not enough just to have shared legal expectations; one also wants those expectations to do well at taking into account situation details known to both A and B. Thus one problem with a simple jury system is that random juries many not know important situation details that are known by both A and B. So each pair A and B might prefer that a case between be judged by a jury chosen from a community closer to them, so that this jury knows more of their shared context.

But you also couldn’t pick jurors who are too closely connected to A and B, as these might not be willing to function as independent jurors. So, for example, if A and B are both in the movie industry, it might make sense to give them a jury from the movie industry, who could then understand movie practices. But maybe not jurors who are currently working on the very same movie as they.

150 years ago, the US had something closer to this simple jury system, as stated laws were few and vague, juries made most decisions, lawyers were cheap and less often needed, and plea bargaining wasn’t yet much of a thing. Since then, US law has accumulated far more detail. Yet little of this detail seems to be an adaptation to a more complex world; most is just random. And we must pay lawyers who learn this detail if we hope to win at court.

Worse, regulations greatly restrict who can be a lawyer, slower more expensive legal processes add to our costs, and few of us have sufficient assets to pay if we lose. Thus US law has rotted in a great many ways. When will we notice that, and consider big changes?

By the way, one feature that we might want in a legal system is an ability ask it for prior approval for behavior. “Would it be legal or not-negligent if I did it this way?” And you might hope that a very detailed legal system could at least offer this advantage over a simple jury-based version. You’d just look up the relevant detailed law. But in fact our very complex detailed legal system doesn’t offer this feature. You just can’t ask what acts might be legal; you can only do stuff and find out later if you are punished.

Added 11a: Jury decisions can vary. To reduce the impact of that in particular parties, we could  have the consequences for them be set by prediction markets on jury decisions. Those market predictions would be far more consistent across cases.

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Want Your Complaint Heard?

People like to complain; social media is full of it. But such complaints seem less than fully satisfying, perhaps because we usually complain to third parties. Maybe what we really want is to know that the target of our complaint heard and understood it. If so, let’s make that possible.

Imagine that you feel a complaint coming on. So you go to YouHurtMe.Com, and navigate down a hierarchy of possible complaint target groups, to reach specific options like “White people who think they aren’t racist”, “Women who think they are too good for a man like me”, or “Students who grade grub to improve a B+”. You could pick larger encompassing target groups, or define some even more specific targets.

Once you find your target group, you next pick your specific complaint, such as “You actually are racist”, “You aren’t as good as you think”, or “Be grateful for your B+”. If you don’t see your complaint listed there, you can add one. Once you’ve declared yourself a complainer of this type, you can browse some essays expressing that complaint, and vote on which essay looks best.

Or you might add your own new essay for consideration. But your essay must be civil, and include at least one multiple-choice comprehension test question at the end.

Targets of complaints can also come to the website. They may sincerely want to hear complaints made against people like them, and want to show those who make such complaints that they’ve heard and understood them. The system asks each new visitor some questions designed to quickly identify complaints targeted at them. (They can refuse to answer some questions.)

They then select a matching complaint, like “You actually are racist”, read the top voted essay, and take the ending comprehension test. Having passed the test, they are now publicly listed among targets who have heard and understood the complaint.

We might want to allow those who’ve heard complaints about them to respond in some way, though perhaps that risks too much acrimony. Less problematically, we might allow compliments as well as complaints to be created and heard via this same structure.

But, bottom line: it seems quite feasible to let complainers know that the targets of their complaints have heard and understood them. Which is what complainers often say is the main thing they want: to be heard.

From a conversation with Agnes Callard.

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Shoulda-Listened Futures

Over the decades I have written many times on how prediction markets might help the intellectual world. But usually my pitch has been to those who want to get a better actionable info out of intellectuals, or to help the world to make better intellectual progress in the long run. Problem is, such customers seem pretty scarce. So in this post I want to outline an idea that is a bit closer to a business proposal, in that I can better identify concrete customers who might pay for it.

For every successful intellectual there are (at least) hundreds of failures. People who started out along a path, but then were not sufficiently rewarded or encouraged, and so then either quit or persisted in relative obscurity. And a great many of these (maybe even a majority) think that the world done them wrong, that their intellectual contributions were underrated. And no doubt many of them are right. Such malcontents are my intended customers.

These “world shoulda listened to me” customers might pay to have some of their works evaluated by posterity. For example, for every $1 saved now that gains a 3% real rate of return, $19 in real assets are available in a century to pay historians for evaluations. At a 6% rate of return (or 3% for 2 centuries), that’s $339. Furthermore, if future historians needed only to randomly evaluate 1% of the works assigned them, then if malcontents paid $10 per work to be maybe evaluated, historians could spend $20K (or $339K) per work they evaluate. Considering all the added knowledge and tools to which future historians may have access, that seems enough to do a substantial evaluation, especially if they evaluate several related works at the same time.

Given a substantial chance (1% will do) that a work might be evaluated by historians in a century or two, we could then create (conditional) prediction markets now estimating those future evaluations. So a customer might pay their $20 now, and get an immediate prediction market estimate of that future evaluation for their work. That $20 might pay $10 for the (chance of a) future evaluation and another $10 to establish and subsidize a prediction market over the coming centuries until resolution.

Finally, if customers thought market estimate regarding their works looked too low, then they could of course try to bet to raise those estimates. Skeptics would no doubt lie waiting to bet against them, and on average this tendency of authors to bet to support their works would probably subsidize these markets, and so lower the fees that the system needs to charge.

Of course even with big budgets for evaluations, if we want future historians to make reliable enough formal estimates that we can bet on in advance, then we will need to give them a well-defined-enough task to accomplish. And we need to define this task in a way that discourages future historians from expressing their gratitude to all these people who funded their work by giving them all an A+.

I suggest we have future historians estimate each work’s ideal attention: how much attention each particular work should have been given during some time period. So we should pick some measure of attention, a measure that we can calculate for works when they are submitted, and track over time. This measure should weigh if the dissertation was approved, the paper was published and where, how many cites did it get, etc. If we add up all the initial attention for submitted works, then we can assign historians the task of (counterfactually) reallocating this total attention across all the submitted works. So to give more attention to some, they’d have to take away attention from others.

Okay, so now they can’t give every work an A+. (And we ensure that bet assets have bounded values.) But our job isn’t done. We also need to give them a principle to follow when allocating attention among all these prior works. What objective would they be trying to accomplish via this reallocation of attention?

I suggest that the objective just be intellectual progress, toward the world having access to more accurate and useful beliefs. A set of works should have gotten more attention if in that case the world would have been more likely to have more quickly come to appreciate valuable truths. And this task is probably easier if we ask future historians to use their future values in this task, instead of asking them to try to judge according to our values today.

These evaluation tasks probably get easier if historians randomly pick related sets of works to evaluate together, instead of independently picking each work to evaluate. And this system can probably offer scaled fees, wherein the chance that your work gets evaluated rises linearly with the price you paid for that chance. There are probably a lot more details to work out, but I expect I’ve already said enough for most people to decide roughly how much they like this idea.

Once there were many works in this system, and many prediction markets estimating their shoulda-been attention, then we could look to see if market speculators see any overall biases in today’s intellectual worlds. That is, topics, methods, disciplines, genders, etc. to which speculators estimate that the world today is giving too little attention. That could be pretty dramatic and damning evidence of bias, by someone, evidence to which we’d all be wise to attend.

One obvious test of this approach would be to assign historians today the task of reallocating attention among papers published a century or two ago. Perhaps assign multiple independent groups, and see how correlated are their evaluations, and how that correlation varies across topic areas. Perhaps repeating in a decade or two, to see how much evaluations drift over time.

Showing these correlations to potential customers might convince them that there’s a good enough chance that such a system will later correctly vindicate their neglected contributions. And these tests may show good scopes to use, for related works and time periods to evaluate together, and how narrow or broad should be the expertise of the evaluators.

This whole shoulda-listened-futures approach could or course also be applied to many other kinds of works, not just intellectual works. You’d just have to establish your standards for how future historians are to allocate shoulda attention, and trust them to actually follow those standards. Doing tests on works from centuries ago here could also help to show if this is a viable approach for these kinds of works.

Added 7am 28Apr: On average more assets will be available to pay for future evaluations if the fees paid are invested in risky assets. So instead of promising a particular percentage chance of evaluation, it may make more sense to specify how fees will be invested, set the (real) amount to be spent on each evaluation, and then promise that the chance of evaluation for each work will be set by the investment return relative to the initial fee paid. Yes that induces more evaluations in state of the world where investments do better, but customers are already accepting a big chance that their work will never be directly evaluated.

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Try-Two Contest Board

Imagine that a restaurant wants to ask its associates (cooks, servers, etc.) what are the best two menu items to put on its menu as specials on a particular night. They have a large set of possible menu items to consider, the measure of success is menu item sales revenue, and they want a mechanism that is both fun and easy. (Which rules out conditional prediction markets, at least for now.)

Here’s an idea. Start with a contest board like this, on a wall near associates:

Continue reading "Try-Two Contest Board" »

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Super Hostile Takeovers

For a brief period in the late ’50s, until the mid-’60s, when modern hostile takeover techniques were perfected, we had a pretty much unregulated market for corporate control. Shareholders received on average 40% over the pre-bid price for their shares. But… 1968 … Williams Act … made it vastly more expensive for outsiders to mount successful tender offers. The highly profitable element of surprise was removed entirely.

The even stronger inhibition on takeovers resulted from actions taken by state legislatures and state courts in the ’80s. The number of hostile tender offers dropped precipitously and with it the most effective device for policing top managers of large, publicly held companies. … now, with the legal power to shift control in the hands of the incumbent [managers], they, rather than shareholders, will receive any premium paid for control. … It should come as no surprise then that, as hostile takeovers declined to 4% from 14% of all mergers, executive compensation started a steep climb. (more)

As this quote shows, current laws make it crazy hard to buy public firms, which has the effect of greatly entrenching CEO power and raising their compensation. Like blackmail laws, this is another way in which law goes out of its way to favor powerful elites. Law pretends to dislike and oppose elite dominance, but key details show otherwise.

Even during U.S. historical period when takeovers were easiest, still “shareholders received on average 40% over the pre-bid price for their shares.” That means those trying to takeover in essence faced a 40% tax; no point in taking over a firm if you can’t make it worth at least this much more. So this most effective device for policing top management would be even more effective if we could cut this tax, so takeovers could help in more cases.

The key problem is that when a takeover attempt starts to buy up lots of stock in a firm, people start to notice and then bid up their prices, expecting that a takeover will improve the value of the firm. Can we fix this problem?

Yes, consider that when the government wants to buy a bunch of land properties to build a project like a road, it faces a similar problem, that after the first few purchases the other property owners will greatly raise their price, knowing that the government can’t do its project without all the needed properties. 

The standard solution to this problem is eminent domain, where the government forces them all to sell at some official “market price”. But, as I’ve discussed, a better solution is to use a Harberger tax, where each property owner must always declare a value for their property, a value which is used both to set their property tax, but also to be an always-available sales price for the property. These values will generally be reasonable, due to owners trying to avoid paying high taxes, allowing the government or any other party to quickly assemble large property bundles for any big project without needing any special powers.

We could use the same trick for stocks. Tax stock ownership, and require every stock owner to declare a value for their stock, a value used both to set their tax, and also available to takeover attempts as a sales price. Then a takeover could happen overnight, as 51% of the stock is suddenly purchased at its declared Harberger tax value.

Most speculators might want to declare a value just above the current stock price, and we’d make it easy for them to just declare a percent increment, like say “My value is always 10% over the current market price.” If most did that, a takeover might only face a 10% tax, instead of the 40% tax described above.

I gotta admit that cases like current policy discouraging hostile takeovers makes me despair of trying to introduce any more complex or less effective innovations. The case for allowing more hostile takeovers seems to me especially simple and strong. If even a change this valuable and simple can’t be done, what hope is there for other policy changes?

Added 3p: The tax seems to be about the same size today, but so the main extra problem now is allowing far fewer takeovers:

In large-sample studies, the winning offer premium typically averages approximately 40%–50% relative to the target price two calendar months before the initial bid announcement. (more)

Of course we should also make it easier for someone who owns 51% of stock to actually control the firm. So not using poison pills, staggered boards, supermajority voting rules, voting vs non voting stock, required prior notice of or plan to purchase, etc.

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Personal Energy Apps

Long ago I noticed that the most successful people I had met also tended to have pretty high personal ‘energy.’ They talked fast, fidgetted, moved around a room more, needed less sleep, could drink more before they collapsed, etc. It seems to me that high energy people are quite visibly impressive to the people around them, and that personal energy is one of the visible features that impresses people most, especially re men.

I’ve talked recently about publishing objective low-dimensional measures of individual health, wealth, and smarts. (And previously on status apps.) These three features seem quite feasible to measure reasonably well when people cooperate in their measurement. But with energy it seems plausible that we could often measure personal energy with high accuracy even without their cooperation.

Sure if they’d let us film them 24/7, that’s probably plenty enough to measure energy well, but we can probably see a lot about energy from just short recordings. For example, student evaluations of  few-second-long videos of teachers without sound correlated substantially with student evaluations of those teachers.

So we could have people evaluate a large dataset of long audio or video recordings, and then use machine learning to find and apply patterns in that to a much larger space of videos. I’d bet a lot of the variance will be explained by some pretty low level features. And then we might have another well-measured feature of people that we wouldn’t have to put quite so much effort into discerning or showing off.

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Lost Advanced Civilizations

Did life on Earth start on Earth, or did it start on Mars and move to Earth? If you frame such panspermia as an “extraordinary claim” for which you demand “extraordinary evidence”, you will of course conclude that this should be treated “skeptically” as unlikely and sloppy unscientific “speculation”. To be disdained and not treated as serious by respectable academics and science journalists. But that’s not really fair.

You see the early Mars environment is, a priori, about as likely a place for life to start as the Earth environment. So if the rate at which life is transferred between the planets were high enough, then equal chances of life starting first in both places would result in equal chances for Earth life to have started in either place. We should take the expected time difference between life starting in the two places, and ask how high is the chance that life would move from one planet to the next during that period. The more often rocks are thrown from one place to the other, and the more easily life could survive for the travel period within those rocks, then the more likely it is that Earth life started on Mars.

In addition, Mars, being further from the Sun, would have cooled first, and had a head start in its window for life. Making it more likely that life would start there and spread to Earth than vice versa. Of course life starting first on Mars would have implications for what we might see when we look at Mars. If we had expected Mars life to continue strong until today, then the fact that we see no life on Mars now would be a big strike against this hypothesis. But if we expected Mars life to have died out or at least gone dormant by now, then the issue is what we will see when we dig on Mars. With enough data on such digs, we may come to reject to Mars first hypothesis even given its initial plausibility.

A similar analysis applies to panspermia from other stars. You might think it obvious that the rate at which life-filled rocks from a star make it to seed other stars is very low, but most stars are born in large groups close together in stellar nurseries. So if life arose early enough within our star’s nursery, there might have been high rates of moving that life between stars in that nursery. In which case the chance that Earth life came from another star could also be high, and the best place to look for life outside our star would be the other stars from our stellar nursery.

Now consider the possibility of lost advanced civilizations. Not just civilizations at a similar level of development to those around them in space and time; that’s quite likely given that we keep finding new previously-unknown settlements and developed places. No, the more interesting claims are about substantial (but not crazy extreme) decreases in the peak or median level of civilizations across wide areas. Such as what happened late in the late Mediterranean Bronze Age, or at the fall of the Roman Empire. Could there have been “higher” civilizations before the “first” ones that we now know about in each region, such as the Sumerians, Egyptians, and Chinese Shang dynasty? (I’m talking human civs, not others.) Continue reading "Lost Advanced Civilizations" »

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Toward A University Department of Generalists

The hard problem then is how to get specialists to credit you for advancing their field when they don’t see you as a high status one of them. (more)

Many of my most beloved colleagues, and also I, are intellectual polymaths. That is, we have published in many different areas, and usefully integrated results from diverse areas. Academia tends to neglect integration and generality, which hurts not only intellectual progress, but also myself and my colleagues. Which makes me especially interested in fixing this problem.

The key problem is that academics and their research are mostly evaluated by those who work on very similar topics and methods. To the extent that these are evaluated by folks at a larger distance, it is by those who control one of the limited number of standard “disciplines” (math, physics, literature, econ, etc.).

Thus we have a poor system for evaluating work and people that sit between disciplines, or that cover many disciplines. Making it harder to evaluate work that combines areas A and B, and maybe also C and D. You might be able to get an A person to evaluate the A parts, and then a B person for the B parts, but that is more work, and the person who knows how to pick a good A evaluator may not know how to pick a good B evaluator. Academics tend to think that interdisciplinary groups do worse work, held to lower standards, and this is a big part of why.

Furthermore, even when specialists can evaluate such things well enough, they have an incentive to say “Maybe that should be supported, but not with our resources.” That is, for people and work that combines A and B, the A folks say it should be supported by the B budget, and vice versa. Often to be accepted by people in A, you must do as much good work in A as someone who only ever works in A, regardless of how much good work you also do in B, C, etc.

Yet generality still gains substantial prestige among intellectuals, which gives me hope. For example, there are usually fights to write more general summaries, such as review articles and textbooks, fights usually won by the highest in status. And Nobel prize winners, upon winning, often famously wax philosophic and general, pontificating (usually badly) on a much wider range of topics than they did previously.

Academic disciplines and departments usually need to do two things: (1) evaluate people to say who can join and stay in them, and (2) train new candidates in a way that makes it likely that many will later be evaluated positively in part (1). I’m not sure there is a way to do part (2) well here, but I think I at least know of a way to do part (1).

I propose that one university (and eventually many) create a Department of Generalists. (Maybe there’s a better name for it.) To apply to join this department, you must first get tenure in some other department. You submit your publication record, and from that they can calculate a measure of the range of your publications. Weighted by quality of course. Folks with very high range are assumed to be shoo-ins, folks with low ranges are routinely rejected, and existing department members have discretion on borderline cases.

How could we calculate publication range? I’ve posted before on using citation data to construct maps of academia. From such maps it seems straightforward to create robust metrics describing the volume in that space encompassed by a person’s research. And something like citations could be used to weigh publications in this metric. No doubt there is room for disagreement on exact metrics, and I’m not pushing to get too mechanical here. My point is that it is feasible to evaluate generality, as we know how to mechanically get a decent first cut measure of a researcher’s range.

So what do people in Department of Generalists do exactly? Well of course they continue with their research, and can continue to serve the departments form which they came. But they are encouraged to do more general research than do folks in other departments. They can now more easily talk with other generalists, work together on more general projects, and invite outside generalist speakers.

Maybe they experiment with training or mentoring other professors at the university to be generalists, people who hope to later apply to join this generalist department. They might be preferred candidates to write those prestigious general summaries, such as review articles and textbooks, and to teach generalist courses, like big introductory courses. And especially to review more generalist work by others.

It would of course be hard work to get such a department going. And you’d need to start it at a university where there are already many generalists who could get along. But I have high hopes, again from the fact that academics so often fight to appear general, as in fighting to write summarizes and to pontificate on more general issues. Once there was a widespread perception that people in the Department of Generalists were in fact better at being generalists, as well as meeting the usual criteria of at least one regular department, they would naturally be seen as an elite. A group that others aspire to join, patrons aspire to fund, reporters aspire to interview, and students aspire to learn under.

And then academia would less neglect work on integration, synthesis, and generality, and work between existing disciplines. Oh academia would still neglect those things, don’t get me wrong, just less. And that seems a goal worth pursuing.

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Missing Model: Too Much Do-Gooding

Grim view of human nature … is mistaken, a persistent and counterproductive myth. … the evidence for mass selfishness is extremely thin. … The surprising truth is that people tend to be­have decently in a crisis. To the British, the all-too-familiar example is the cheerful demeanour of Londoners during the Blitz. … New Orleans after Hurricane Katrina … rumours ran wild about the murder and rape of children inside the Louisiana Superdome; but when the national guard showed up, … met instead by a nurse asking for medical supplies. (more)

Friday I asked the author of a pandemic novel what he thought went most wrong in his fictional world. He said selfishness: blaming others, and not sacrificing enough to protect others from infection. He also said he was surprised to see people acting less selfishly than he predicted in our real pandemic.

As the above quote indicates, that’s a common mistake. In this pandemic I estimate that the bigger problem is people pushing for too much “helping”, rather than too little. That’s a common problem in health and medicine, and this poll says 2-1 that it is the more common problem:

Of course my Twitter followers are probably unusual by this metric; I’d bet most think selfishness is the bigger problem. One reason is that it can look suspiciously selfish to say there’s too much do-gooding, as if you were trying to excuse your selfish behavior. Another reason is that the theory of selfishness is simpler. In economics, for example, we teach many quite simple game theory models of temptations to selfishness. In contrast, it seems harder to explain the core theory of why there might be too much do-gooding.

This seems to suggest a good and feasible project: generate or identify some good simple game theory models that predict too much do-gooding. Not just personal signaling acts that do too much, but acts that push collective norms and decisions toward too much do-gooding. I’d be happy to help with such a project. Of course it would make only a small contribution to the problem, but still I’d guess one worth the trouble.

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