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Bullshit title. from the original blog post: > masking gender had no effect on interview performance > it appeared that men who were modulated to sound like

Bullshit title. from the original blog post: > masking gender had no effect on interview performance > it appeared that men who were modulated to sound like women did a bit better than unmodulated men and that women who were modulated to sound like men did a bit worse than unmodulated women. Though these trends weren’t statistically significant

Bromskloss 10y ago
In both the title and in the passages you quote, we would have been better served by being told _how big_ the difference was.
- mynewtb 10y ago
  > weren't statistically significant
  - Bromskloss 10y ago
    No, give me the numbers first and foremost, and let me draw my own conclusions.
    - PeterisP 10y ago
      That's the whole point - the proper conclusion is "the numbers are meaningless, the experiments we did cannot provide any opinion about the existence, magnitude and direction of such differences", and any conclusions you might draw from seeing some specific numbers would make you less informed than you are right now.
      - Bartweiss 10y ago
        That's not true at all. "Less than significant" is not "the numbers are meaningless", it's "the arbitrary threshold p=.05 was not met". p=.049 is not magic, p=.051 is not worthless. They have far more in common than either does with p=.011, and claiming that giving out specific numbers would make things worse is absurd. I agree that it's bad practice to go "hey, p=.09, but it could be meaningful!" But it's at least as bad to say "we cannot provide any opinion about... such differences". That's simply false, you can provide data and confidence about the topic.
      - lmm 10y ago
        An experiment not finding a statistically significant difference can mean something very different depending on what the power of the experiment was.
      - marcosdumay 10y ago
        To what extent were the numbers meaningless? And how big was the unproven but probably effect so somebody else can try to verify it? Or even not try, discarding it as irrelevant because it was too small? And the most important question that every statistical study should answer: What effect magnitudes were discarded by this research? Claiming insignificant results and refusing to share them is telling your audience "well, we learned something, but we'll hide our findings from you because you are just too stupid to even imagine the kind of thing we learned here." Yes, for some audiences that would be true, but it's something a researcher shouldn't even imagine telling somebody. It's basically incompatible with the kind of thoughts required from researchers.
    - marvin 10y ago
      Not statistically significant means that it is exceedinly likely that the difference was simply due to randomness in the subject selection, and that no difference in fact exists. At this point you're just reviewing the researchers' methodology.
      - Bromskloss 10y ago
        > At this point you're just reviewing the researchers' methodology. That is absolutely part of it.
kabouseng 10y ago
Not statistically significant already says you cant say much about the observation. But here is a thought, what if woman already get preferential treatment (contrary to what many feminist would have you believe), and when their voices are masked as a mans, that preferential treatment falls away. And vica versa for when mens voices are masked as a womans. And this whole rickmarol is about achieving equal outcomes (even distribution of women to men in tech), and not about equal opportunities or the removal of bias / prejudice.
- gbersac 10y ago
  > what if woman already get preferential treatment I always felt it was the case. IT is such a man place that every one is happy when a woman come, even if she is a little bit less efficient compared to men. Myself included. So I am biased to favour women.
  - namaemuta 10y ago
    Just a question for you: do you feel happy when a woman comes to work with you because of what she can contribute or because she is a woman? I read a statement that reflects this very well: "when a woman is treated different, it doesn't mean she is treated better".
    - visarga 10y ago
      Could be just a preference for diversity. There are already tons of men in IT.
      - xexers 10y ago
        Agreed. If you think about the 2 extremes... it's not ideal to work in an office with 100% men or 100% women... for very different reasons (which I won't list here).
      - rthrewmr 10y ago
        Our society was sold the idea that diversity would be beneficial for productivity. When and why did we stop valuing the end and instead value the means?
Timshel 10y ago
Especially since later on : > “Once you factor out interview data from both men and women who quit after one or two bad interviews,” she writes, “the disparity goes away entirely.”
cwmma 10y ago
And even those trends went away when you controlled for people leaving the site after having less interviews implying that if there was a trend it was due to practice.
MustardTiger 10y ago
Did they give the actual data so we could see if it was statistically significant or not? Lots of blog posts proclaim things to be or not be statistically significant but have no basis for their proclamation and don't know statistics at all.
deleted 10y ago
[deleted]

Bromskloss 10y ago

In both the title and in the passages you quote, we would have been better served by being told _how big_ the difference was.

mynewtb 10y ago
> weren't statistically significant
- Bromskloss 10y ago
  No, give me the numbers first and foremost, and let me draw my own conclusions.
  - PeterisP 10y ago
    That's the whole point - the proper conclusion is "the numbers are meaningless, the experiments we did cannot provide any opinion about the existence, magnitude and direction of such differences", and any conclusions you might draw from seeing some specific numbers would make you less informed than you are right now.
    - Bartweiss 10y ago
      That's not true at all. "Less than significant" is not "the numbers are meaningless", it's "the arbitrary threshold p=.05 was not met". p=.049 is not magic, p=.051 is not worthless. They have far more in common than either does with p=.011, and claiming that giving out specific numbers would make things worse is absurd. I agree that it's bad practice to go "hey, p=.09, but it could be meaningful!" But it's at least as bad to say "we cannot provide any opinion about... such differences". That's simply false, you can provide data and confidence about the topic.
    - lmm 10y ago
      An experiment not finding a statistically significant difference can mean something very different depending on what the power of the experiment was.
    - marcosdumay 10y ago
      To what extent were the numbers meaningless? And how big was the unproven but probably effect so somebody else can try to verify it? Or even not try, discarding it as irrelevant because it was too small? And the most important question that every statistical study should answer: What effect magnitudes were discarded by this research? Claiming insignificant results and refusing to share them is telling your audience "well, we learned something, but we'll hide our findings from you because you are just too stupid to even imagine the kind of thing we learned here." Yes, for some audiences that would be true, but it's something a researcher shouldn't even imagine telling somebody. It's basically incompatible with the kind of thoughts required from researchers.
  - marvin 10y ago
    Not statistically significant means that it is exceedinly likely that the difference was simply due to randomness in the subject selection, and that no difference in fact exists. At this point you're just reviewing the researchers' methodology.
    - Bromskloss 10y ago
      > At this point you're just reviewing the researchers' methodology. That is absolutely part of it.

kabouseng 10y ago

Not statistically significant already says you cant say much about the observation. But here is a thought, what if woman already get preferential treatment (contrary to what many feminist would have you believe), and when their voices are masked as a mans, that preferential treatment falls away. And vica versa for when mens voices are masked as a womans. And this whole rickmarol is about achieving equal outcomes (even distribution of women to men in tech), and not about equal opportunities or the removal of bias / prejudice.

gbersac 10y ago
> what if woman already get preferential treatment I always felt it was the case. IT is such a man place that every one is happy when a woman come, even if she is a little bit less efficient compared to men. Myself included. So I am biased to favour women.
- namaemuta 10y ago
  Just a question for you: do you feel happy when a woman comes to work with you because of what she can contribute or because she is a woman? I read a statement that reflects this very well: "when a woman is treated different, it doesn't mean she is treated better".
  - visarga 10y ago
    Could be just a preference for diversity. There are already tons of men in IT.
    - xexers 10y ago
      Agreed. If you think about the 2 extremes... it's not ideal to work in an office with 100% men or 100% women... for very different reasons (which I won't list here).
    - rthrewmr 10y ago
      Our society was sold the idea that diversity would be beneficial for productivity. When and why did we stop valuing the end and instead value the means?

Timshel 10y ago

Especially since later on : > “Once you factor out interview data from both men and women who quit after one or two bad interviews,” she writes, “the disparity goes away entirely.”

cwmma 10y ago

And even those trends went away when you controlled for people leaving the site after having less interviews implying that if there was a trend it was due to practice.

MustardTiger 10y ago

Did they give the actual data so we could see if it was statistically significant or not? Lots of blog posts proclaim things to be or not be statistically significant but have no basis for their proclamation and don't know statistics at all.

deleted 10y ago

[deleted]