In our information overloaded age, censorship no longer works as well as it used to. From the NSA, to Ferguson, to DNLee, to attempts to muzzle reports on climate change, we see one theme recurring over and over again: people using channels previously inaccessible to them to tell their stories. Attempts to silence them have only made the story all the more compelling, made it spread faster and further, as it did for DNLee.
This is undeniably a good thing. But we are seeing something arise in its place: the flood of irrelevant or useless information to drown out the signal within the noise. "Climategate" - a scandal manufactured by pulling microscopic bits of emails pulled from years-worth of correspondence, and then quoting them out of context - added far more confusion to the climate change "debate" than did any attempt at blanket censorship. In Ferguson, the timed reveals of Mike Brown's pot use and shoplifting somehow masqueraded as information relevant to understanding his death.
Sociological questions: about the success of minorities and women in technical fields or within the academy, about economic development in poor countries, or poor communities in rich countries, or about the prevalence of sexual assault just about anywhere - are hard questions. They are hard from a technical standpoint because they involve complex systems with millions or interacting components, where the answer can change depending on what exactly what question you ask, and what you include in your sample. They are also hard because they are emotionally charged, and the pre-existing biases of the researcher - which we all have because we are all human beings - can affect the outcome.
I believe it is the responsibility of scientists and science communicators to be honest about the limits and caveats of their work. As I have written before, full disclosure and honesty can open up conversations that ultimately reveal deeper truth. The way NOT to do it is to it prepend idle speculation and personal biases with some science to make it look as though everything you have to say is backed by research.
The best recent example of this is Nicholas Wade's book "A Troublesome Inheritance" (I will not provide a link), in which he devotes five chapters to an ultimately irrelevant primer on human genetics, only to veer into purely speculative writing about sociological differences between races. The irrelevant and obvious "science" really amounts to the fact that people from geographically close locations share more genes than people from geographically distant locations. This is used as a smokescreen to give Wade space to speculate -without evidence - that race explains all sorts of sociological differences, from poor economic development in African countries to the fact that "Jews are good at capitalism."
Today we see another example of this in Wendy M. Williams and Stephen J. Cici's New York Times op-ed "Academic Science Isn't Sexist." The article includes a link to a PDF of their "forthcoming" paper "Women in Academic Science: A Changing Landscape" (I have to wonder how they pulled this off. Normally papers are embargoed from media coverage until publication. And normally, scientists don't cover their own work in a New York Times op-ed). Like Wade's book, the article really consists of two parts. The first is (somewhat) grounded in science:
They are more likely to receive hiring offers, are paid roughly the same (in 14 of 16 comparisons across the eight fields), are generally tenured and promoted at the same rate (except in economics), remain in their fields at roughly the same rate, have their grants funded and articles accepted as often and are about as satisfied with their jobs. Articles published by women are cited as often as those by men. In sum, with a few exceptions, the world of academic science in math-based fields today reflects gender fairness, rather than gender bias.First, as noted by Emily Willingham, the caveats "roughly", "generally", and "about" refer to real, statistically-significant differences between men and women. The honest assessment of the data would be to say that they found evidence of institutional sexism, but that it was - in their opinion - a small effect.
From there, the op-ed veers into pure speculation.
As children, girls tend to show more interest in living things (such as people and animals), while boys tend to prefer playing with machines and building things. As adolescents, girls express less interest in careers like engineering and computer science.What? This assertion is not based on the paper - at all. There is no citation or link, and I'm well aware this isn't taken for granted by sociologists, educators or anyone. There is no warning that we've moved from discussing something that's at least partially grounded in research to something that appears to be purely an opinion.
Furthermore, as Jonathon Eisen points out, the fact that tenure, promotion, pay, and peer-review appear to be (almost) fair says nothing about workplace harassment, mistreatment, abuse, etc. etc. etc. They did not look at these issues, and other (actual) evidence paints a very different picture (why not mention this hard data, especially when they don't have any?). Yet Cici and Williams seem to lump both these types of issues together. Evidence that pay has at least come a long way toward equalization is hardly evidence that there is no sexual abuse or harassment in academic science.
For me, the op-ed can be summarized by its final sentence: "We are not your father's academy anymore." The word "we" is very revealing: perhaps the authors - part of the academy themselves - feel some frustration at people who just won't shut up about the problems inherent in the current system. Perhaps it is not your father's sexism: there's no pin-up girls in the lab and Francis Crick isn't going to grope you and steal your data (but only because he's dead). But with the new censorship comes the new prejudice: the prejudice that attempts to disguise itself with the thinnest veneer of data. The prejudice that pretends that some progress means we've come far enough, or perhaps too far.
I'll close with this video of Neil DeGrasse Tyson, in response to a question about why women are badly represented in the sciences. "Before you start talking about genetic differences [or lifestyle choices, for that matter], you've gotta come up with a system where there's equal opportunity. Then we can have that conversation."