Relevant and even prescient commentary on news, politics and the economy.

Different but Equal?

Here’s a fascinating recent article with the forbidding title of The landscape of sex-differential transcriptome and its consequent selection in human adults.  I’ll provide the abstract, and then a translation into English.  Here’s the abstract:

Background
The prevalence of several human morbid phenotypes is sometimes much higher than intuitively expected. This can directly arise from the presence of two sexes, male and female, in one species. Men and women have almost identical genomes but are distinctly dimorphic, with dissimilar disease susceptibilities. Sexually dimorphic traits mainly result from differential expression of genes present in both sexes. Such genes can be subject to different, and even opposing, selection constraints in the two sexes. This can impact human evolution by differential selection on mutations with dissimilar effects on the two sexes.

Results
We comprehensively mapped human sex-differential genetic architecture across 53 tissues. Analyzing available RNA-sequencing data from 544 adults revealed thousands of genes differentially expressed in the reproductive tracts and tissues common to both sexes. Sex-differential genes are related to various biological systems, and suggest new insights into the pathophysiology of diverse human diseases. We also identified a significant association between sex-specific gene transcription and reduced selection efficiency and accumulation of deleterious mutations, which might affect the prevalence of different traits and diseases. Interestingly, many of the sex-specific genes that also undergo reduced selection efficiency are essential for successful reproduction in men or women. This seeming paradox might partially explain the high incidence of human infertility.

Conclusions
This work provides a comprehensive overview of the sex-differential transcriptome and its importance to human evolution and human physiology in health and in disease.

The article was interesting, but a slog given my lack of knowledge of the field.  I don’t mind admitting I couldn’t follow it in its entirety, though  I did manage to acquire a feeling of inadequacy and the start of a headache. So for a translation, I will rely on distinguished geneticist Jenny Graves who just wrote a piece about the article that is quite accessible and from which I will quote below. Graves starts with the punchline:

Most of us are familiar with the genetic differences between men and women.

Men have X and Y sex chromosomes, and women have two X chromosomes. We know that genes on these chromosomes may act differently in men and women.

But a recent paper claims that beyond just genes on X and Y, a full third of our genome is behaving very differently in men and women.

These new data pose challenges for science, medicine and maybe even gender equity.

Here’s a more extensive summary:

In their new paper, the authors Gershoni and Pietrokovsk looked at how active the same genes are in men and women. They measured the RNA produced by 18,670 genes in 53 different tissues (45 common to both sexes) in 544 adult post mortem donors (357 men and 187 women).

They found that about one third of these genes (more than 6,500) had very different activities in men and women. Some genes were active in men only or women only. Many genes were far more active in one sex or the other.

A few of these genes showed sex biased activity in every tissue of the body. More commonly, the difference was seen in one or a few tissues.

Most of these genes were not on sex chromosomes: only a few lay on the Y or the X.

How could a third of our genes be differently controlled in men and women?

We now understand that proteins work in extensive networks. Change the amount of one protein produced by one gene, and you change the amounts of all the proteins produced by many genes in a long chain of command.

We also know that hormones have powerful influences on gene activity. For instance, testosterone and estrogen dial up or down many genes in reproductive and body tissues.

Here is how Graves’ piece ends:

What do these new insights mean for our progress toward gender equity? A bad outcome could be appeals to return to outdated sexual stereotypes. A good outcome will be recognition of sex differences in medicine and treatment.

I think what Graves is after can be characterized as “different but equal.” And though it makes perfect sense given the current state of genetics and biology (to say nothing of common sense), such a philosophy would be quite unwelcome in certain parts these days.

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On the Effect of the Gender Composition of the Editorial Boards for Top Economics Journals

Here’s the abstract of a discussion paper from the IZA Institute of Labor Economics by Felix Bransch and Michael Kvasnicka:

Using data on articles published in the top-five economic journals in the period 1991 to 2010, we explore whether the gender composition of editorial boards is related to the publishing success of female authors and to the quality of articles that get published. Our results show that female editors reduce, rather than increase, the share of articles that are (co-)authored by females. We also find evidence that female editors benefit article quality at low levels of representation on editorial boards, but harm article quality at higher levels. Several robustness checks corroborate these findings. Our results are broadly consistent with existing evidence on the behavior of gender-mixed hiring committees and of relevance for gender equality policy.

The rest of the article is also at the link.

Consider this post to be a follow up to this one.

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Random Thoughts on the Google Memo

I haven’t been following the Google Memo saga all that closely, but I do have some random thoughts about the whole brouhaha:

1. If the distribution of skillsets, interests and temperament is the same between men and women, why do the latest figures (June 24, 2017) from the Bureau of Prisons indicate that 93.3% of federal prisoners are men?
2. Would a rational person, upon learning that 93.3% of federal prisoners are men, jump to the conclusion that our legal system won’t punish women for crimes?
3. If the distribution of skillsets, interests, and temperament is the same between men and women, why does Google give advertisers an option to target customers by gender? Shouldn’t they stop?

I note… this post was suggested by my wife. She asked my opinion about the topic, I made the three points above, and she said: “This sounds like it should be a post.” So here it is.

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Shootings by Police Officers: Self-Control and More

I stumbled on a recent paper in the Police Quarterly entitled “Quick on the Draw: Assessing the Relationship Between Low Self-Control and Officer-Involved Police Shootings.”

The authors are Christopher M. Donner, Jon Maskaly, Alex R. Piquero, and Wesley G. Jennings from Loyola, U of Texas at Dallas, U of Texas at Dallas and U of South Florida, respectively.

Quoting from the paper:

While the extant literature on police use of deadly force is voluminous, it is fairly limited with regard to the influence of officer characteristics. Moreover, this is the first known study to explore an individual-level criminological theory(i.e., self-control) in the context of police officer-involved shootings. In building on previous studies linking low self-control to negative police behavior more generally (Donner et al., 2016; Donner & Jennings, 2014), this study uses data from a sample of 1,935 Philadelphia police officers to investigate the extent to which Gottfredson and Hirschi’s (1990) general theory can predict officer-involved shootings specifically.

Based on theory and related research, it is hypothesized that officers with lower levels of self-control will be more likely to have used deadly force because police shooting incidents would provide low self-control officers (those who are more impulsive, self-centered, short-sighted, thrill-seeking, and easily provoked) with an opportunity to engage in a behavior that it is often spontaneous, can provide immediate gratification, is adrenaline-inducing, and can provide an outlet for frustration.

Methods
Data and Sample
In this study, we use data collected by Greene et al. (2004) for an National Institute of Justice (NIJ)-sponsored study on police integrity in the PPD. The initial collaboration between Temple University and the PPD began in an effort to help create an information system that would assist the PPD with integrity oversight. To aid this process, baseline information concerning possible predictors of negative police behavior was needed. The data set includes background files, academy training records, and personnel information for 2,094 police officers across 17 academy classes from 1991 to 1998. Due to missing files and incomplete academy training among some officers, the final sample of cases included 1,935 officers. Additional methodological details may be found in Greene et al. (2004).

On average, the sample was almost 27 years of age (range: 18–55), and approximately two thirds of the sample was male. There was virtually equal representation among White (44.5%) and Black (46.0%) officers, and the sample included a smaller number of Hispanic (7.4%) and other race or ethnicity (2.1%) officers. The average education level and length of service was 13 and 3 years, respectively. About one fifth (21%) of the sample was married and one tenth (10.9%) had a parent who served in law enforcement. Additional descriptive statistics may be found in Table 1.

The paper goes on:

Dependent Variable
Greene et al. (2004) were granted access to various databases maintained by the PPD Internal Affairs Division and Police Board of Inquiry. Specifically, these databases contained information relating to, among other things, citizen complaints, officer-involved shootings, other internal investigations, and depart-mental disciplinary actions. These data were collected in the Year 2000; thus,officers in the sample had been out of the police academy for roughly 2 to 9 years. The outcome variable of interest in this study, police shootings, is measured dichotomously (0 = No; 1 = Yes) and reflects whether an officer had ever been involved in a police shooting in which they discharged their firearm.

The primary independent variable, low self-control, was constructed from selected behavioral indicators contained within an officer’s Personal Data Questionnaire (PDQ).2 Individuals, who apply to be a Philadelphia Police Officer and pass the entrance examination, are referred to the Background Unit of the police department. Here, qualified applicants are given a PDQ.The PDQ collects self-reported background information, including among other things the applicant’s identifying information, family background, residence history, educational history, employment history, credit history, military record, motor vehicle history, adult and juvenile criminal history, and drug-use history. This information is validated through an interview with a background investigator, a full background investigation, and subsequently a polygraph examination.

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