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Strip mining is very apt if you view the economics of the present system as "effort -> recognition -> career advancement". Even in strip mining, the resources that had been buried are now available for use in the broader economy. What's no longer available is the living that was to be had digging them out.
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The problem isn't effort, though. All of the things I mentioned constitute effort and could be rewarded. The job economy was created by mathematicians incentivizing the proof of difficult theorems above all else and valuing all other work at approximately zero as far as career advancement was concerned. Now they're pulling a 180 and claiming that math was never really about proving theorems, but that's contradicted by their revealed preferences. The strip-mining problem only exists if they continue with the status quo ante.
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Mathematicians aren't homogeneous. There are mathematicians valuing pedagogy, collaboration, bridge-building, theory building, along with those that chase the 'difficult theorems', to name a few, and there are lots of flavors within each class, with lots of blending and blurring. You infer that mathematicians prefer the status quo simply because it is the status quo -- with a little thought, you'll recognize that this is a fairly silly notion.

There are myriad circumstances where the values of most practitioners differ from the status quo, which is nevertheless well-entrenched. This can arise from inertia, or from outside forces, such as broader cultural milieu, integration with larger institutions, or contending with economic realities. If you think that these do not and haven't historically played a role in determining the job economy and that math is a pure field where mathematicians could comfortably shape it according solely to their own ideals then you are naive

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And, in addition, many mathematicians are graduate students or postdocs hoping to line up a permanent job soon.

For example, if you look at Terry Tao's blog, he has a tremendous amount of first-class expository writing. So, too (to some extent) do junior mathematicians -- but, unfortunately, this tends to not be highly valued by the job market. Grad students and postdocs have learned that to succeed they need to play by the existing rules of the game.

Well, the board has just been yanked from underneath them. People like me can afford the sort of idealism and soul-searching that the parent comment describes, but junior mathematicians face a very unenviable set of circumstances.

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1) I never said the problem was effort; I was trying to explain the strip mining analogy, and it's one of the two anchors that make the analogy work.

2) Mathematicians didn't create this economy; it was foisted upon them by the same managerial mentality that brought us "publish or perish" and "the monthly sales quota".

3) I can't tell if you honestly don't get why the strip-mining analogy resonates, or...?

Here's another analogy: if we suddenly discovered personal teleportation, and marathon runners were complaining that it was ruining the sport, would you say "they're pulling a 180 and claiming that marathon running was never really about getting to a point 26 miles away as fast as possible, but that's contradicted by their revealed preferences"?

The strip mining analogy is better though, because it captures the sense of irreversible goal-loss when a problem goes from being "unsolved" to "solved".

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As far as I understand, even with "publish or perish", peer reviewers decide what counts as an important enough paper to be published in a prestigous journal, and committees of peers decide whether or not, say, an expository article on arXiv or a textbook counts toward hiring or tenure. Again, as far as I understand, those things have largely not been rewarded in the past.

I like your marathon example, but maybe not for the reasons you intended. The community of marathoners decides the rules of a marathon. You don't need a hypothetical teleporter; you're already not allowed to use a bicycle, performance-enhancing drugs, or shoes that don't fit the specifications. The rules are updated to adapt to changing technology. Yes, I'm arguing that the strip-mining analogy doesn't make sense because mathematics is in the same situation. There's nothing stopping peer reviewers and hiring/tenure committees from changing the rules about which kinds of effort confer recognition and career advancement.

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Strip mining is an extraordinarily appropriate metaphor.

Imagine a mine has an unknown number of rare materials. And you know the general location of a few of the most valuable spots. But you don't know what may be valuable right next to it. If the pieces that we know are valuable are suddenly gone, the incentive to mine that particular area drops considerably, dropping the chance to discover potentially brand new materials that would have been found the normal way.

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That's an empirical claim. I could equally well say that doing an automated search of the problem space and having a database of results and open problems will identify vastly more interesting and valuable areas. Again, the idea that math is some exhaustible material is a metaphor, not an established fact. I'm willing to change my view as new evidence comes in, but I think we're going to have to wait and see what the landscape looks like in a few years.
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> the incentive to mine that particular area drops considerably, dropping the chance to discover potentially brand new materials that would have been found the normal way.

FWIW, I think the metaphor breaks down with this framing. This isn't really a problem associated with strip mining, what's left behind is generally low or negative value (toxic). I'd suggest a different metaphor, from Wikipedia:

> This process involves the removal of all ground vegetation in the area, which is a detriment to the environment.[19] Topsoil may be placed over the tailing along with planting trees and other vegetation. Another reclamation method involves filling in the hole with water to create an artificial lake. Large tailing piles left behind may contain heavy metals which can leach out acids such as lead and copper and enter into water systems.

This feels very similar to the issues with algorithmic problem "mining". It has the potential to destroy the human ecosystems surrounding these problems, leaving barren wasteland behind where nothing can grow or flourish.

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