Prickly Women

The Inside Higher Ed blog just had a short opinion article by M. Soledad Caballero and Aimee Knupsky at Allegheny College about the praise of “Prickly Women.”  A quote from the article appears below.

Why academe should honor prickly women (opinion)

They are known throughout history as the “killjoys,” the “ice queens,” the “hysterics,” the “ball-busters.” They are the “Prickly Women” — the women who don’t let things go, who stand up for themselves and others, and who question the status-quo of structural inequities and outdated institutional practices. They stick out decidedly among the “bro-hood” of academic administration.

Despite the negative connotations and perceptions they incite, Prickly Women have exactly the kind of insight and persistence needed as the crises in higher education continue to mount.

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Time-to-parity for women publishing in STEM fields

A recent paper by Holman et al. in PLOS Biology presents a new look at the gender gap in publications for millions of authors from over one hundred countries in over six thousand journals.  You can interact with the data through their  web app.

The gender gap in science: How long until women are equally represented?
Luke Holman, Devi Stuart-Fox, Cindy E. Hauser, PLOS Biology 2018.

The authors present the current author gender ratio, its rate of change per year, and the estimate number of years until the gender ratio comes with 5% of parity.  A few notes below the image…

Here are the first things I noticed:

  1. The estimated percent of women authors “maxes out” at 50% (there’s a Figure 2 that includes fields with a higher percentage of women).
  2. arXiv.org – the preprint server that began as a mathematics and physics venue – has particularly poor percent of women authors.
  3. First author percentages tend to be “ahead of the curve” for each discipline, while last authors lag behind the numbers for all authors.  In many fields, first authors denote who did the most work, and last authors denote who funded the work.  My hunch is that a higher proportion of women get papers as graduate students and postdocs, whereas fewer women make it to senior-level faculty as heads of a lab.
  4. On a positive note, more women are publishing in the fields than before (the rate of change is mostly positive).

The paper’s supplementary figure S3 shows data for Computer Science (from arXiv).  Based on current trajectories, only two sub-categories (Information Theory and Robotics) hope to see gender parity within the next 50-100 years.  We still have a long way to go.

Changing Demographics of the Biomedical Workforce

Thanks to Mike the Mad Biologist’s blog, this article (from January 2017) resurfaced:

The new face of US science : Nature News & Comment

This study looks at census data to determine the demographics of PhD recipients in the biological or medical sciences.  The authors characterize a biomedical workforce that is fundamentally different from previous generations.  Their infographic contains the main trends:

web-graphic-biomedical

Heggeness et al, The new face of US science. Nature Comment, 2017

 

 

 

Racism in academia – not surprisingly, it’s everywhere

Zuleyka Zevallos, an applied sociologist who does policy research in Australia, just wrote an excellent blog post about racism in academia.  While it speaks directly to researchers and faculty, it’s worth a read for anyone.

Racism in Research and Academia – The Other Sociologist  by Dr. Zuleyka Zevallos

Ruth Simmons, President of PVAMU

I was excited to see that Ruth Simmons, former president of Smith College (1995-2000) and Brown University (2002-2012), has been named as the permanent president of Prairie View A&M University.

via Now in Her 70s, First Black Ivy-League President Finds a Third Act – The Chronicle of Higher Education

While I never met Ruth Simmons while I was at Brown, I saw images of her frequently on the Brown CS0931 page in 2012:

Screen Shot 2017-10-24 at 11.03.03 AM

The course, Introduction to Computation for the Humanities & Social Sciences, taught computational thinking to non-computational undergraduate majors.  Each year, the undergraduate TAs design the course page around a theme.  I was an instructor for CS0931 in the spring of 2012, when students created the page as an homage to Dr. Simmons in her last year as president of the university.  The Staff page is particularly fun.   Dr. Simmons clearly left an impression on the undergraduates at Brown University, and I bet she’ll do the same at Prairie View A&M.

 

 

Breakdown of CS faculty hires in 2017

Craig E. Wills of WPI recently wrote a report that describes the outcomes of advertised CS faculty positions across institutions in 2017. It was a follow-up to a previous report on the CS positions advertised in 2017.  The report contains a wealth of information about the number of faculty positions filled at different institutions.

In summary, 244 of the 323 advertised positions were fulfilled, giving an aggregate 75% success rate.  Not surprisingly, this success varied by institution type: 90% of the positions advertised by the top 100 graduate schools according to U.S. News Rankings were filled, whereas other PhD-granting institutions, Masters-granting institutions, and Bachelors-granting institutions had 67%, 66%, and 69% success rates, respectively.

Wills also looked at the faculty positions by research area.  I’ll focus on three:

  • AI/DM/ML: artificial intelligence, computational linguistics, data mining, machine learning, natural language processing, text analytics
  • CompSci: computational biology, computational life science, computational medicine, computational neuroscience (you get the picture…)
  • Security: cryptography, forensics, information assurance, privacy, security

The figure below shows the percent of faculty positions sought for each field on the x-axis and the percent of faculty positions filled for each field on the y-axis:

faculty-positions-fig3

Points that lie on the red x=y line indicate that the percent of faculty positions filled exactly matched the percent of faculty positions sought.  Let’s look at the three largest outliers:

  • AI/DM/ML was sought for 11% of the positions by area, but ended up filling 21% of the positions.
  • DataSci was sought for 16% of the positions by area, but ended up filling only 7% of the positions.
  • Security was sought for 23% of the positions, but ended up filling only 12% of the positions.

Wills cited many factors associated with these discrepancies, including the fact that nearly a quarter of the positions did not specify an area of interest in their ad.  Additionally, institutions simply did not end up hiring in the areas of interest, either because they could not find candidates in that area or they found better candidates in other areas.  Areas could also be satisfied with multiple fields (for example AI/DM/ML or DataSci accounted for 27% of the positions sought and ended up filling 28% of the positions when combined).

Another factor that Wills considered was the number of Ph.D.s produced by area (based on Taulbee Survey results):

faculty-positions-fig5

It’s good to be in Security, since only 6% of the Ph.D.s produced are in this area compared to the demand of 23% of the positions sought in this area.  It’s also good to be in AI/DM/ML because over 20% of the faculty positions were filled in this area, even if the job ads didn’t specify it.

Overall, the report was an interesting read – I’m looking forward to seeing these trends over time.