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This is a tactic that I've yet been able to counter effectively. It's more about mixing levels of rigor. Case in point: a tech company releases diversity numbe

by aristus 12y ago

This is a tactic that I've yet been able to counter effectively. It's more about mixing levels of rigor. Case in point: a tech company releases diversity numbers. A reasonable point is to ask for a breakdown into tech, admin, support, etc. Often in these companies the diversity is shoved into sales and marketing. But then another commenter will ask about the diversity of the candidates, and speculate that they are identical to the company's hires, and then "prove" that the company's practices are unbiased. So then you point out that a company is not a blushing maid, that they choose the people they recruit, project an image that influences self-selection, and heavily encourage people to refer their friends. And then you get attacked for demanding too much rigor. What the argument is really about is whether there is a problem to fix. The diversity numbers clearly indicate that there is. But people who like to believe there is not alternately dig trenches and build walls of rigor to block the debate.

yummyfajitas 12y ago
What the argument is really about is whether there is a problem to fix. The diversity numbers clearly indicate that there is. You can't draw a normative conclusion from a positive claim alone. You additionally need some normative axiom. No fact can tell you what you should do. In the discussion you cite, the disagreeing parties have different normative axioms. Some people believe in statistical equality as an end goal, whereas others have equal treatment. If you believe in statistical equality (as I think you do), then the facebook numbers are a problem to fix. If you believe in equality of treatment (as I suspect the others do), then you can draw no conclusion - the numbers do not directly imply anything about equal treatment. Similarly, consider a debate between a "meat is murder" activist and a carnivore. No one disagrees that animals are killed - the only disagreement is over whether that's a bad thing.
- aristus 12y ago
  A good example of the debate and tactics I'm describing. :) If you agree that women are not somehow less mentally capable than men, then the fact that technical jobs are 85% dominated by men should be a concern. Not just for "normative" reasons or "statistical equity", but simply that there are a lot of talented people being excluded for one reason or another. If not, you should explain WHY not. Anomalies demand explanation. You dismiss the numbers because of an assumed equality of treatment and saying, well, I don't see anything therefore it's not a problem... and if it is, it's somebody else's problem. That's exactly the mismatch of rigor I'm talking about. You put the burden on others to "prove" that something is amiss, then when they do, demand more.
  - yummyfajitas 12y ago
    Claiming that "a lot of talented people being excluded for one reason or another" is a positive claim. It's merely a fact about the world. If you are against this, that's a normative axiom (or possibly a normative conclusion derived from another normative axiom). As for the undue rigor involved, it's you who seems to be demanding a lot: you demand proof that men and women are statistically unequal merely to admit it as a possibility. More precisely, let A = "women are unequally treated" and B = "women are not statistically equal to men" (at the point of application for Facebook employment). The diversity numbers imply A || B. You are assuming that B is false because there is no proof it is true, and therefore concluding A must be true (since A || B and !B => A). But strangely, you are not asserting that A is false without a rigorous proof that A is true (which would imply B). That's the fundamental asymmetry that Scott Alexander is talking about. The people you disagree with are merely saying "A || B, we don't know which."
    - aristus 12y ago
      "We don't know which", and will stop there. That's fine. All I ask is you be explicit about where you stand: on the side of the status quo, not wrapped in the flag of math as you would like pretend, but simply content with the way things are, and utterly incurious about how to change it. [edit] For fuck sake - if you had noticed a 50% imbalance in CPU usage on your server farm, surely you'd spend some time trying to understand it. What the hell is wrong with so many people who are busy inventing facile excuses and dredging up mathy reasons why to NOT recognize the problem as a problem and looking into why it might exist?
      - yummyfajitas 12y ago
        If I narrowed the source of CPU usage down to this block of code: for { x <- f() y <- g() } yield (x+y) I would not immediately conclude that f() is the source of the problem. That's what you are advocating doing. And if someone suggests g() might be the problem, you are assuming they are wrong and demanding an excess level of rigor from them. That's exactly what Scott Alexander is warning against. [edit: I'm sticking to epistemology. I'm not hijacking the thread to discuss gender.]
im3w1l 12y ago
So basically it goes like this. 1. Hypothesis: Women are discriminated in tech. 2. Argument: There are less women in tech. (shows number of women in tech) 3. Counter argument: There are less applicants.(shows number of applicants, number of uni students) 4. Counter counter argument: They self-select out of tech because of the discrimination. Afaik, there is solid evidence for points 2&3. What is the evidence for 4?

by aristus 12y ago

yummyfajitas 12y ago

What the argument is really about is whether there is a problem to fix. The diversity numbers clearly indicate that there is. You can't draw a normative conclusion from a positive claim alone. You additionally need some normative axiom. No fact can tell you what you should do. In the discussion you cite, the disagreeing parties have different normative axioms. Some people believe in statistical equality as an end goal, whereas others have equal treatment. If you believe in statistical equality (as I think you do), then the facebook numbers are a problem to fix. If you believe in equality of treatment (as I suspect the others do), then you can draw no conclusion - the numbers do not directly imply anything about equal treatment. Similarly, consider a debate between a "meat is murder" activist and a carnivore. No one disagrees that animals are killed - the only disagreement is over whether that's a bad thing.

aristus 12y ago
A good example of the debate and tactics I'm describing. :) If you agree that women are not somehow less mentally capable than men, then the fact that technical jobs are 85% dominated by men should be a concern. Not just for "normative" reasons or "statistical equity", but simply that there are a lot of talented people being excluded for one reason or another. If not, you should explain WHY not. Anomalies demand explanation. You dismiss the numbers because of an assumed equality of treatment and saying, well, I don't see anything therefore it's not a problem... and if it is, it's somebody else's problem. That's exactly the mismatch of rigor I'm talking about. You put the burden on others to "prove" that something is amiss, then when they do, demand more.
- yummyfajitas 12y ago
  Claiming that "a lot of talented people being excluded for one reason or another" is a positive claim. It's merely a fact about the world. If you are against this, that's a normative axiom (or possibly a normative conclusion derived from another normative axiom). As for the undue rigor involved, it's you who seems to be demanding a lot: you demand proof that men and women are statistically unequal merely to admit it as a possibility. More precisely, let A = "women are unequally treated" and B = "women are not statistically equal to men" (at the point of application for Facebook employment). The diversity numbers imply A || B. You are assuming that B is false because there is no proof it is true, and therefore concluding A must be true (since A || B and !B => A). But strangely, you are not asserting that A is false without a rigorous proof that A is true (which would imply B). That's the fundamental asymmetry that Scott Alexander is talking about. The people you disagree with are merely saying "A || B, we don't know which."
  - aristus 12y ago
    "We don't know which", and will stop there. That's fine. All I ask is you be explicit about where you stand: on the side of the status quo, not wrapped in the flag of math as you would like pretend, but simply content with the way things are, and utterly incurious about how to change it. [edit] For fuck sake - if you had noticed a 50% imbalance in CPU usage on your server farm, surely you'd spend some time trying to understand it. What the hell is wrong with so many people who are busy inventing facile excuses and dredging up mathy reasons why to NOT recognize the problem as a problem and looking into why it might exist?
    - yummyfajitas 12y ago
      If I narrowed the source of CPU usage down to this block of code: for { x <- f() y <- g() } yield (x+y) I would not immediately conclude that f() is the source of the problem. That's what you are advocating doing. And if someone suggests g() might be the problem, you are assuming they are wrong and demanding an excess level of rigor from them. That's exactly what Scott Alexander is warning against. [edit: I'm sticking to epistemology. I'm not hijacking the thread to discuss gender.]

im3w1l 12y ago

So basically it goes like this. 1. Hypothesis: Women are discriminated in tech. 2. Argument: There are less women in tech. (shows number of women in tech) 3. Counter argument: There are less applicants.(shows number of applicants, number of uni students) 4. Counter counter argument: They self-select out of tech because of the discrimination. Afaik, there is solid evidence for points 2&3. What is the evidence for 4?