Women don't speak up!

Katie Coffman has a new paper forthcoming in the QJE on Evidence on Self-Stereotyping and the Contribution of Ideas

The abstract reads:
"We use a lab experiment to explore the factors that predict an individual's decision to contribute her idea to a group. We find that contribution decisions depend upon the interaction
of gender and the gender stereotype associated with the decision-making domain: conditional
on measured ability, individuals are less willing to contribute ideas in areas that are stereotypically outside of their gender's domain. Importantly, these decisions are largely driven by
self-assessments, rather than fear of discrimination. Individuals are less confident in gender
incongruent areas and are thus less willing to contribute their ideas. Because even very knowledgeable group members under-contribute in gender incongruent categories, group performance suffers and, ex post, groups have difficulty recognizing who their most talented members are. Our results show that even in an environment where other group members show no bias, women in male-typed areas and men in female-typed areas may be less influential. An intervention that provides feedback about a woman's (man's) strength in a male-typed (female-typed) area does not significantly increase the probability that she contributes her ideas to the group. A back-of-the-envelope calculation reveals that a lean in style policy that increases contribution by
women would significantly improve group performance in male-typed domains."

Here's the killer figure: The Probability of a Missed Opportunity: that is, someone knew the right answer, but their answer wasn't chosen and intead the group got the answer wrong (because the person knowing the answer didn't speak up enough or the other too much).

For each score (i.e. how many answers they got correct in a test in that category), the chance a man (black) or a woman (light grey) with that score had a missed opportunity.

The figure below is for Male Typed Categories (Environmental science, Sports, History, Geography)

So, women with a perfect score (5) in a male typed category, have a higher chance to have a missed opportunity than men with a score of 1 out of 5. 

The best women just have a barely lower chance to not miss an opportunity compared to men who got everything wrong. 

More fun with google

I've written before about google searches and gender

Here's a link to an article with the same idea:

The starting point is the following search...

here's another nice one 

Google actually wrote to the guy about the "english major who taught herself calculus" correction.

"We saw your tweet — just wanted to reach out and explain a bit here.

If you search for “taught himself calculus” (in quotes), you’ll see it’s a particularly popular phrase on the web, appearing about 282,000 times — because there’s a popular story out there that Einstein taught himself physics as a teenager (and a recent news story that a kid in Indiana did too). “Taught herself calculus” appears only around 4,000 times. So when Google sees two phrases like this and one is much more common, it may suggest it as a possible alternate search. It’s more complex than that, but that’s essentially why you’re seeing this result. (Darn you, Einstein!)"

Getting more out of science

There has been a lot of activity recently on how to ensure we don't get sidetracked by wrong, or non-robust results.

A recent NYtimes post by Brendan Nyhan on this is quite good: To Get More Out of Science, Show the Rejected Research

He writes:

"The intense competition for space in top journals creates strong pressures for novel, statistically significant effects. As a result, studies that do not turn out as planned or find no evidence of effects claimed in previous research often go unpublished, even though their findings can be important and informative."

"This pattern of publication bias and failed replications, which is drawing attention in fields from psychology to medicine, has prompted great alarm within the scientific community. "

"Others advocate requiring the registration of trials before data has been collected. For instance, some social scientists have voluntarily begun to preregister analysis plans for experiments to minimize concerns about selective reporting. Unfortunately, the demand for statistically significant results is still likely to create publication bias. For example, federal law and journal policies now require registration of clinical trials, but publishing of trial results has been found to be selective, to frequently deviate from protocols and to emphasize significant results. "

His solution:

"Instead, my colleagues and I propose a radically different publishing model: Ask journal editors and scientific peers to review study designs and analysis plans and commit to publish the results if the study is conducted and reported in a professional manner (which will be ensured by a second round of peer review)."

Funnily enough, this comes up again and again in experimental economics. And most often when people think about controversies, and when they got annoyed that their paper, which had such a nice design, didn't get a good publication just because the results weren't maybe as exciting as one could hope for...

I actually don't agree. There are many ways in which an interesting design can deliver results that are not interesting. The problem is, it is often easier to detect whether a result was achieved for the wrong reasons (though that may not always be very easy) than why an expected result did not happen. And there could be many boring reasons for an expected result that did not happen. An extreme example is that somehow things were so complicated that everything just turned out to be very noisy. Think of running your perfect design but using only subjects who actually don't understand your language. The results of the best design might not be worth publishing, and correctly so.

Likewise, many designs that we thought were not interesting may actually turn out to be very interesting and important. Not everyone will have the same intuition. 

Two new books on gender

Tyler Cowen writes in the NYtimes about Why the Economic Gender Gap Will Eventually Close

"The first book, “Why Gender Matters in Economics” (Princeton University Press, 2014) by Mukesh Eswaran, an economics professor at the University of British Columbia, draws on data from past economic studies conducted under laboratory conditions to show how gender influences financial actions and relationships."

I actually got that book in the mail, I may write about it later. 

"In sum, these research results suggest that women are perceived as easier to take advantage of in a variety of economic settings. That’s the bad news, and it comes from measuring a difference in gender behavior at a specific point in time."

Tyler is more optimistic about the second book “The Silent Sex: Gender, Deliberation and Institutions” (Princeton University Press, 2014) by Christopher F. Karpowitz, professor of political science at Brigham Young University, and Tali Mendelberg, professor of politics at Princeton.

"Drawing upon data from politics, business meetings and behavior in the corporate boardroom, they portray a society where women participate less in many public settings, especially those in which real power is exercised. This links up with the experimental results described in Mr. Eswaran’s book, because an underparticipating group that doesn’t resist discrimination is more likely to suffer.

This sounds gloomy so far. But the authors show that once women achieve a critical mass in a particular area, their participation grows rapidly, at least after basic norms of inclusion have been established."

In german we say "His word in God's ear". I'm ready to be surprised...

New Academic Year, New blogging...

Hi all, I'll try to start blogging somewhat regularly again, now that we're in the new academic year.

Let it be a good one to you all!