Tuesday, May 24, 2016
Pull up a chair.
I just finished reading Why Women Earn Less: Just Two Factors Explain Post-PhD Pay Gap by Helen Shen in Nature. It's based on a recent study by Catherine Buffington et al (2016) that examines data obtained from the UMETRICS project at the University of Michigan. Both Buffington et al (2016), Nature, and a similar commentary in Science do a serious disservice to the human race and academia by publishing and commenting on the study in its present form.
Firstly, it has been known for many years that the pipeline problem for women in STEM, of which the pay gap is a component, is the result of a gradual accumulation of negative effects (Valian, 1998). Studies such as Buffington et al (2016) that examine too short a time-frame are likely to seriously distort the influences of factors that contribute. Although both Mason and Weinberg mention problems with time frame durations, even five to ten years is not long enough. She Figures 2015 (European Commission, 2015; Figure 6.1), as one example, shows that predominant effects of gender occur over a more prolonged time window.
Secondly, let's examine data selection and statistics. Buffington et al (2016) lump together variables that have intersectional effects such as race and age, and omit categories with potential for insight such as single mothers or fathers with childcare responsibilities. There are other variables not scored in the original data sets such as sexual orientation and couples that chose not to declare their relationship status.
The authors also appear to disregard graduate students that for reasons of insufficient support, harassment, locational restrictions, or otherwise not fitting the traditional academic mold, dropped out during their graduate years in spite of substantial investment in training. In addition, the study neglects undergraduate students that failed to be admitted to graduate programs due to financial and location-specific stressors, or merit-based, ivory tower biases (Goldrick-Rab & Kendall, 2016). These longitudinal biases reflect societal stressors associated with race, gender, class, disability, age and veteran status that result in substantial downward spirals over time. Thus, even though Buffington et al (2016) include some key variables in their study, their inclusion in this short time frame without regard for interactions is nothing short of misrepresentation.
Another problem of data selection and representation concerns the numbers for gender. Many studies, including the European Commission Report, have indicated that the numbers of PhDs granted to women and men are nearly equal in recent years. The fact that there are more than double the number of men in Buffington et al (2016) calls the UMETRICS and Census Bureau's Protected Identification Key (PIK) data into serious question. Numbers for other variables such as race are not reported — the percentages mentioned in the Methods show Black and Hispanic populations are negligiblely accounted for. Because least squares regression aims to minimize the overall variation, the numbers representing variables such as gender and race will affect the results.
Third, I would like to point to an effect that goes unnoticed by Buffington et al (2016), perhaps unsurprisingly given the normalization of sexist bias in societies across the world; namely, women consistently shoulder the burden and blame for motherhood, or lack thereof. Quoting Buffington et al, "Nineteen percent of females and 24 percent of males had children at the time of the 2010 census." A five percent difference in parental status is, in the words of Buffington regarding other observations, a robust effect. More importantly, the observation suggests more men 'get pregnant' than women. Considering the effect of motherhood on women's careers, the finding could further be taken to imply that men are conditioned by capitalist patriarchal expectations to neglect their wives and children. It's beyond time capitalist patriarchy acknowledge and accept responsibility for its share of care.
Finally, Buffington et al (2016) claim that the large majority of the pay gap in their study is accounted for by choice of STEM field. However, they neglect to mention other studies (see Miller, 2016; Slaughter, 2015; and Short Takes on Slaughter in Signs, 2016 ) showing the devaluation of fields as more women are accepted and vice versa.
The titles and recognition resulting from the Nature and Science commentaries also will undoubtly contribute to the longevity of the interpretation and citational rankings. It's likely to cause a serious waste of research dollars, result in unnecessary delays, and negatively affect the lives of dedicated women researchers in STEM all over the world. What a shame.
...A more formal rebuttal will be submitted after I'm finished with my move.
Posted by 真行 at 15:09
Sunday, May 8, 2016
What is intersectionality? Intersectionality is when two or more biases or prejudices interact in such a way that an individual is marginalized or omitted from consideration of the effects of either.
The harmful effects of intersectionality are most obvious for the combination of gender and race. Due to Crenshaw's (1989) examination of United States anti-discrimination law and, more importantly, the frequency and potential extensiveness of harm and marginalization, black feminism has a unique claim to intersectionality. The reason should be obvious. In terms of bias, the effects of race and gender operate instantaneously based on appearance. I include all women of color: Black, Asian, Latina, Indian and Aboriginal women in the westernized world and colonized countries; though the intersectional effects of gender and race are location-specific and, therefore, also apply to Nepalese and Asian women in the Middle East and Rohingya in Myanmar to name a few non-western examples.
I grew increasingly aware of the intersectional effects of race and gender while reading and signing petitions, though initially I hadn't read enough of the current work in feminism to have a term for it. One petition was for a black college professor that had been manhandled, thrown down on the asphalt, and arrested for trying to avoid sidewalk construction on university grounds after dark. I observed all of her hard work disappear in the blink of an eye. Since then I've read more stories than I can count. Black women arrested for failing to signal a turn. Black women arrested for bringing a child along for a job interview given on short notice, in spite of being hired. Black women arrested for self protection. It took more than six months for the energy of #BlackLivesMatter to include women with the addition of #SayHerName. It took years for the disappearance, assault and murder of indigenous women to raise an eyebrow (Elwood, 2016; Huntley, 2015; Chief Elk-Young Bear, 2015). The intersection of different legal jurisdictions and the effect of race and class assumptions on data collection and statistical analysis are particularly relevant for considering the potential for harm and the complexity of issues that must be taken into account. For women of color, intersectionality is readily observed by the instantaneous transformation of seemingly trivial circumstances into matters of life and death.
It is not that intersectionality does not operate elsewhere, in a variety of circumstances. Implicit and explicit biases and their intersectional effects are part of how minds work. Death and imprisonment are very visible results. Death and imprisonment are easily obtainable statistics. Yet intersectionality is a process that can render attributes legally non-functional in determination of underlying causes (Crenshaw, 1989; Elwood, 2016). Moreover, in the current age of big data and data science, proprietary black-boxed algorithms could easily hard-wire discriminatory practices based on race and gender (Executive Office of the President, 2016). The attentional delay or omission in investigation of matters of women is particularly worrisome.
Marginalization due to intersecting bias is constantly happening and has long term cumulative effects that remain invisible to many of those operating within the bounds of "white" capitalist patriarchal institutions. As noted by Ahmed (2014), "Patriarchy: it’s quite a system. It works. Whiteness too: it works...Whiteness is invisible to those who inhabit it. For those who don’t inhabit it, whiteness appears as a solid" Or as "bricks" that accumulate to build "walls" that require extra affective and physical labor that not only goes unnoticed and uncredited, but for which individuals are further penalized.
There are a number of characteristics that can operate intersectionally with gender besides race. Characteristics that are instantaneously "visible" and have gender-specific intersectional effects are age and disability. There also are characteristics about which a person can, to some extent, choose to be "visible": class, sexual orientation, religion, weight and language. These characteristics are not necessarily instantaneously identifiable in the same way as race. These are characteristics about which individuals are claimed to have a 'choice'. Muslim women might choose to wear a hijab because of their religion and/or for a sense of safety and belonging to their community. By wearing the hijab they are doing their best to create their equivalent of a "white" space, at least within their community. What safety and community can the western world provide that would overcome racial bias?
For Caucasian women in the west, bricks and walls are realized more gradually since their operation has been normalized by society and within communities and institutions. Bricks and walls can masquerade as 'choices.' For white women navigating the boundaries of white patriarchy deleterious effects can go unnoticed or disregarded for quite some time, if recognized at all. Sexism, abuse and motherhood are examples. The citation practices discussed by Ahmed are another*.
Due to years of concerted effort shared by women and feminists world-wide (including some men), the western world is beginning -- only beginning and in ways dependent on race and socio-economic status -- not to disadvantage women for the care-work of parenting. Slaughter's (2015) Unfinished Business discusses the undervaluing of care work typical in society. The critiques that follow in Signs and Dissent highlight some of the serious differences as a function of class. But nowhere, nowhere, do I see mention of the fact that a woman of color can be arrested for bringing her child along for a job interview, a "choice" that was the best that could managed under the circumstances. (Few people would argue that paid employment at a living wage wouldn't substantially improve quality of care over the long term.) Nowhere, nowhere, do I see mention that officials of Detroit saw fit to remove children from their parents care because of water shutoffs due to the failure to pay a $100-$200 bill, when corporations in the area owed hundreds of thousands. At the same time that middle- and upper-class parenting is beginning to receive some consideration, black and indigenous women and families are criminalized for short falls in the care of governments, society, and white patriarchal systems (Jaffe, et al, 2014; Banchiri, 2016). Welfare-to-Work and Right-to-Work programs aren't a living wage -- especially with children and the tearing apart of families and support systems by the additional criminalization of black and indigenous fathers. Worse yet, the end cost to society in terms of child care, foster care, psychiatry, lawyer fees and the prison industrial complex is much greater than the cost of a living wage or Universal Basic Income for every child born would be.
Today I am not a mother and all the community and conversation that represents. Yet by whose choice? If you've read my pipeline posts, your answer might not be as immediate.
*Although a writer in the humanities might be able to choose to cite only women, that choice is not available for women in STEM, especially given the multi-authorship of so many papers under the competitive pressures for multi-disciplinarity in increasingly corporatized academia and funding agencies.
Posted by 真行 at 03:18