Archive for discrimination

“the U.S. census needs a different race question”, does it?

Posted in Books, Statistics, Travel with tags , , , , , , , on March 31, 2020 by xi'an

“The stated aim — at least for the last half century — [of the census race question] is to help policy makers and demographers assess whether members of different racial groups have equal access to housing, education, employment and other services, as mandated by law.”

A fairly interesting tribune in Science News on the U.S. census race question and the feature that people often self-identify with a category with “doesn’t always match the box someone else might have checked for them”. The discussion focus on failing to protect discriminated groups because people from said discriminated groups do not identify as members of said discriminated groups. Or, because of a genetic ancestry test like 23andme, people from non-discriminated groups do identify as members of a particular discriminated group, e.g., native American Indians. And while there is a separate question on whether or not the respondant is of Hispanic, Latino or Spanish origin, a third of those answering in the affirmative tick the “other race” box in the census. While the sociologist whose work inspired this article calls for different questions in the census, towards a better reflection of actual discrimination, nowhere is the notion of “race” defined or explicited in this paper. Which may be related to the fact that there is no scientifically accepted such definition, as discussed in this UN report. Except all of us belonging to the Homo sapiens sapiens subspecies and descending from common ancestors in Africa.

I thus wonder at the relevance at keeping such a confusing entry in a census: in several European countries including France, it is actually illegal to collect statistics about the race, ethnicity, religion or ancestry. Given the above confusion in the US census and no clear solution to redress the observed biases, discrimination should be fought on sounder bases…

Australian theocracy

Posted in Kids, pictures, Travel with tags , , , , on December 25, 2019 by xi'an

Examples from The Guardian at which discrimination based on religious arguments should become legal in Australia:

  • A doctor may tell a transgender patient of their religious belief that God made men and women in his image and that gender is therefore binary (EM)

  • A single mother who, when dropping her child off at daycare, may be told by a worker that she is sinful for denying her child a father (Public Interest Advocacy Centre)

  • A woman may be told by a manager that women should submit to their husbands or that women should not be employed outside the home (PIAC)

  • A student with disability may be told by a teacher their disability is a trial imposed by God (PIAC)

  • A person of a minority faith may be told by a retail assistant from another religion that they are a “heathen destined for eternal damnation” (PIAC).

  • A Catholic doctor refusing to provide contraception to all patients (EM) or to prescribe hormone treatment for gender transition (Equality Australia, Just Equal, LGBTI Health Alliance)

  • A Catholic nurse who refused to participate in abortion procedures (EM) or to provide the morning-after pill to a woman admitted to hospital after a sexual assault (Equality Australia)

  • A pharmacist refusing to provide the pill to women for contraceptive use (EM), or hormone treatment (Public Interest Advocacy Centre, LGBTI Health Alliance)

  • A doctor could refuse to prescribe post-exposure prophylaxis (PEP) within the required 72-hour window to a patient whose condom broke during a sexual encounter on the basis of religious beliefs that forbid sexual activity outside of marriage (Equality Australia)

  • A psychiatrist could say to a woman with depression that “she should be looking forward to the kingdom of heaven”. (Equality Australia)

  • A Jewish school may require that its staff and students be Jewish and accordingly refuse to hire or admit someone because they were not Jewish (EM)

  • A student attends the same religious school through their primary and secondary education. At 16 they lose faith in the religion of the school and tell a teacher that they are now agnostic. The school would be able to expel, suspend or otherwise punish, for example, give detention to the student (PIAC)

  • A homeowner seeking a tenant for their spare room may require that the tenant be of the same religious belief or activity as the homeowner (EM).

against homophobia, transphobia & biphobia

Posted in Statistics with tags , , , , on May 17, 2019 by xi'an

how a hiring quota failed [or not]

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , , on February 26, 2019 by xi'an

This week, Nature has a “career news” section dedicated to how hiring quotas [may have] failed for French university hiring. And based solely on a technical report by a Science Po’ Paris researcher. The hiring quota means that every hiring committee for a French public university hiring committee must be made of at least 40% members of each gender.  (Plus at least 50% of external members.) Which has been reduced to 30% in some severely imbalanced fields like mathematics. The main conclusion of the report is that the reform has had a negative impact on the hiring imbalance between men and women in French universities, with “the higher the share of women in a committee, the lower women are ranked” (p.2). As head of the hiring board in maths at Dauphine, which officiates as a secretarial committee for assembling all hiring committee, I was interested in the reasons for this perceived impact, as I had not observed it at my [first order remote] level. As a warning the discussion that follows makes little sense without a prior glance at the paper.

“Deschamps estimated that without the reform, 21 men and 12 women would have been hired in the field of mathematics. But with the reform, committees whose membership met the quota hired 30 men and 3 women” Nature

Skipping the non-quantitative and somewhat ideological part of the report, as well as descriptive statistics, I looked mostly at the modelling behind the conclusions, as reported for instance in the above definite statement in Nature. Starting with a collection of assumptions and simplifications. A first dubious such assumption is that fields and even less universities where the more than 40% quota was already existing before (the 2015 reform) could be used as “control groups”, given the huge potential for confounders, especially the huge imbalance in female-to-male ratios in diverse fields. Second, the data only covers hiring histories for three French universities (out of 63 total) over the years 2009-2018 and furthermore merges assistant (Maître de Conférence) and full professors, where hiring is de facto much more involved, with often one candidate being contacted [prior to the official advertising of the position] by the department as an expression of interest (or the reverse). Third, the remark that

“there are no significant differences between the percentage of women who apply and those who are hired” (p.9)

seems to make the all discussion moot… and contradict both the conclusion and the above assertion! Fourth, the candidate’s qualification (or quality) is equated with the h-index, which is highly reductive and, once again, open to considerable biases in terms of seniority degree and of field. Depending on the publication lag and also the percentage of publications in English versus the vernacular in the given field. And the type of publications (from an average of 2.94 in business to 9.96 on physics]. Fifth, the report equates academic connections [that may bias the ranking] with having the supervisor present in the hiring committee [which sounds like a clear conflict of interest] or the candidate applying in the [same] university that delivered his or her PhD. Missing a myriad of other connections that make committee members often prone to impact the ranking by reporting facts from outside the application form.

“…controlling for field fixed effects and connections make the coefficient [of the percentage of women in the committee] statistically insignificant, though the point estimate remains high.” (p.17)

The models used by Pierre Deschamps are multivariate logit and probit regressions, where each jury attaches a utility to each of its candidates, made of a qualification term [for the position] and of a gender bias most surprisingly multiplying candidate gender and jury gender dummies. The qualification term is expressed as a [jury free] linear regression on covariates plus a jury fixed effect. Plus an error distributed as a Gumbel extreme variate that leads to a closed-form likelihood [and this seems to be the only reason for picking this highly skewed distribution]. The probit model is used to model the probability that one candidate has a better utility than another. The main issue with this modelling is the agglomeration of independence assumptions, as (i) candidates and hired ones are not independent, from being evaluated over several positions all at once, with earlier selections and rankings all public, to having to rank themselves all the positions where they are eligible, to possibly being co-authors of other candidates; (ii) jurys are not independent either, as the limited pool of external members, esp. in gender-imbalanced fields, means that the same faculty often ends up in several jurys at once and hence evaluates the same candidates as a result, plus decides on local ranking in connection with earlier rankings; (iii) independence between several jurys of the same university when this university may try to impose a certain if unofficial gender quota, a variate obviously impossible to fill . Plus again a unique modelling across disciplines. A side but not solely technical remark is that among the covariates used to predict ranking or first position for a female candidate, the percentage of female candidates appears, while being exogenous. Again, using a univariate probit to predict the probability that a candidate is ranked first ignores the comparison between a dozen candidates, both male and female, operated by the jury. Overall, I find little reason to give (significant) weight to the indicator that the president is a woman in the logistic regression and even less to believe that a better gender balance in the jurys has led to a worse gender balance in the hirings. From one model to the next the coefficients change from being significant to non-significant and, again, I find the definition of the control group fairly crude and unsatisfactory, if only because jurys move from one session to the next (and there is little reason to believe one field more gender biased than another, with everything else accounted for). And for another my own experience within hiring committees in Dauphine or elsewhere has never been one where the president strongly impacts the decision. If anything, the president is often more neutral (and never ever imoe makes use of the additional vote to break ties!)…

freedom to discriminate???

Posted in Statistics with tags , , , , , , on November 18, 2018 by xi'an

“Gay students and teachers could be rejected by religious schools under changes to anti-discrimination laws being recommended by a federal review into religious freedom.” The Guardian, 9 Oct. 2018

The quote is not speaking of one of the 72 countries in the World where homosexuality is considered a crime (with 13 states applying the death penalty), but of Australia, ranked 8th on the Economist 2017 Democracy Index, where religious freedom arguments are legally recognised as a right to discriminate against homosexual students and staff. (As an aside, Australia still has a blasphemy law.)

“While the panel accepted the right of religious school to discriminate against students on the basis of gender identity or sexual orientation, it could see no justification for a school to discriminate on the basis of race, disability, pregnancy or intersex status.” The Sydney Morning Herald, 9 Oct. 2018

I find it flabbergasting that such newspeak inversions (also found in the French “Manif pour tous” slogans turning égalité into a discrimination argument against homosexual weddings and adoptions) can find their way into a legislative text. And more generally that religions can still continue to promote gender discrimination with no consequences.

repeal!

Posted in Kids with tags , , , , , , , , on May 24, 2018 by xi'an

Martin Luther King Jr. (1929-1968)

Posted in Statistics with tags , , , , , , , , , on April 4, 2018 by xi'an