guest post: black boxes and wishful intelligibility

Here’s the one-sentence version of this post: Black-boxing is good, actually. 

(The longer version is a summary of my recent paper, “Wishful Intelligibility, Black Boxes, and Epidemiological Explanation,” just out in Philosophy of Science.) 

Black box explanations get a bad rap: they are opaque, often the result of statistical (rather than canonically “experimental”) causal inference, and self-consciously, well, not the whole truth. Probably because of this, philosophers of science often take for granted the idea that it’s a good thing to “fill in” a black box explanation with more causal detail. In particular, lack of mechanistic evidence is sometimes considered a shortcoming of epidemiological explanations, which often rely on sophisticated observational causal inference methods.

sex as a social construct

What do people, including bioscientists, mean when we say “sex is a social construct?” That’s weird, right? Sex is about biology, isn’t it? Sometimes people hear “social construct” and think “random thing totally unrelated to anything else that we can just change willy-nilly.” That’s the “Blank Slate” position, and it’s a strawman. It is not what people actually mean when we say “sex is socially constructed.” We mean something way cooler and more legitimate.

what is a field?

The following is a guest post by Joe Karaganis.

Thanks to  Jeff Lockhart for inviting this post.  Over the past couple years, he and I have discussed, on and off, the technical and ethical issues surrounding the development of statistical accounts of gender balance in the curriculum of different fields — potentially using data from Open Syllabus, which I direct.

I don’t want to focus on that here, however.  I’ll defer to Jeff’s excellent discussion of the issue from last summer and simply note a couple of our hand-coded forays into the topic with respect to business school assignments and assigned movies.  (In both cases, the percentage of assigned titles attributable to women is around 10%.)  Instead, I’d like to explore a question that has motivated Open Syllabus since its early days: What is a field?  I’m aware of the sociological history surrounding this question but will stick, mostly, to our brutally simple version of it, which for me begins with a story.

who writes social science?

Both the academy generally and the social sciences specifically are rife with inequality. Black and Latine people are underrepresented among sociology PhDs and faculty; people who’s parents have PhDs are dramatically overrepresented; women are awarded less grant funding than men; and academia can be a hostile environment for LGB and especially trans scholars. Yet, despite considerable interest in these issues, it is remarkably difficult to study demographic inequality in critical parts of the academy like publishing for the simple reason that the necessary data either do not exist or cannot be linked. The NSF collects data on students and faculty. Professional associations collect data on members. But journals and publishers generally don’t collect and share data on authors. Christin Munsch and I are changing that.

automated petition signatures with google forms

Since the graduate student strike and related protests by faculty, staff, and undergraduates at the University of Michigan in Fall 2020, I’ve noticed that open letters and petitions in google docs and signed through google forms seem to have replaced slower, more traditional petition technologies for (at least campus) social movements. Having signatures from a google form automatically and instantly appear at the end of an open letter is pretty straightforward, but I wasn’t able to find a good guide for it. So in the “unruly sociologist” spirit of this blog, here is my lay person’s guide to automatic signatures in a petition using google docs and forms.

http://alphastockimages.com

sexism as origin, not accident

[note: this post mentions rape and eugenics]

One of the most prominent proponents of the scientifically inaccurate idea that “male and female brains” are biologically, categorically distinct went on a podcast this week and retracted some of his rhetoric. That’s great news! But in his retraction, Simon Baron-Cohen says people incorrectly jump to the conclusion that his is a “very sexist theory” because they “haven’t bothered reading the book” or his articles. He’s wrong there—reading closely reveals plenty of evidence for sexism as the origin of his theory—but it raises a larger issue. Baron-Cohen is right that reading the original text is important, that the history of science and ideas matters. Without it, modern incarnations of eugenics, phrenology, scientific sexism, and more are able to present themselves as new and progressive ideas.

In this #exclusive #breaking interview, @sbaroncohen clarifies his position on his controversial extreme male brain theory “I think today is a useful opportunity to publicly retract some of that language about male & female brains”
#neurodiversity
⬇️⬇️⬇️https://t.co/3PAkyQJYIN pic.twitter.com/gDfNkRapj7

— John Offord (@johnofford808) November 24, 2020

ai gender bias and computational social science

Gender bias is pervasive in our society generally, and in the tech industry and AI research community specifically. So it is no surprise that image labeling systems—tools that use AI to generate text describing pictures—produce both blatantly sexist and more subtly gender biased results. Our new paper, out now and open access in Socius, adds more examples to the growing literature on gender bias in AI. More importantly, it provides a framework for researchers seeking to either investigate AI bias or to use potentially biased AI systems in their own work.

Two images of U.S. Members of Congress with their corresponding labels as assigned by Google Cloud Vision. On the left, Steve Daines, Republican Senator for Montana. On the right, Lucille Roybal-Allard, Democratic Representative for California’s 40th congressional district. Percentages next to labels denote confidence scores of Google Cloud Vision.

2008 & the sociology job market

It looks like we’re in another “economic downturn,” and many PhDs are understandably worried about what it means for the future of the sociology job market. I haven’t been to Delphi or stayed at a Holiday Inn Express, but I am knee-deep in historical ASA reports. Here’s what the data look like for how the 2008 recession affected the sociology job market in the US. Spoiler: I don’t think the market ever recovered, and more hopeful estimates say it took 4 years to recover.

scatterplot gets a new banner

Scatterplot has a new logo! About time, since we’ve had the last one since December, 2016. Here’s the story behind our new banner and a brief history of scatterplot banners back to our launch in 2007.

blueprint for what?

[Content notice: discussion of rape, genocide]

Last spring, Nicholas Christakis published his latest book, Blueprint: The Evolutionary Origins of a Good Society. The title already sets the stage for some old-fashioned biological determinism.¹ For anyone familiar with evolutionary psychology, it is 520 pages of mostly the same claims, logic, and citations as any other recent evopsych writing aimed at a general public readership. He’s a fan of Steven Pinker’s theses in Enlightenment Now and Blank Slate, and Pinker’s endorsement is prominent on the front cover of Blueprint. For those unfamiliar, the field is riven with “just-so stories,” or simplistic, largely unverifiable assertions about our evolutionary past that justify modern stereotypes and inequalities. The New Yorker summarizes and historicizes this pattern well. When it makes normative claims, evopsych tends to engage in the same is/ought fallacy that structural functionalism did: whatever we observe people doing must serve some necessary function—or else it wouldn’t have evolved—and so whatever is, ought to be. Social reformers beware: you’re meddling with forces beyond your comprehension and fighting against human nature.