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Faculty Diversity & Hiring

In a previous post, I had indicated that more diverse departments (social sciences, math, and business) generally have an above average number of students per term. In this post, I want to discuss issues in diversifying faculty. Why? My faculty union recently tweeted this image

While the expression of solidarity with fellow academics is important, the optics of the image is just plain bad. The lack of racial and ethnic diversity in the photo is real problem. One long-time union leader indicated to me that this is a long-standing problem with our organization.

In this post, I would like to look at how lack of diversity happens – at least on my campus. While administration gives departments lines, it is ultimately up to departments to put in the effort (if that’s what they really want to do) and hire more faculty of color. At the same time, faculty searches are complicated. It is hard to say exactly why a single search turned out the way that it did. However, we can see patterns across multiple searches. So here is my analysis of faculty hiring and diversity in my College of Liberal Arts and Sciences using available data.

Using the College’s annual newsletter, I looked at new tenure track hires (or temporary conversions) between 2012 and 2018. In this 7-year period of time 12 out of 15 departments gained tenured track faculty. I’m using the term “gained tenured track” rather than hire, because – I estimate – a large number of these professors were temporary/adjunct faculty at one point. I have also chosen to obscure the names of the departments to reduce blowback. However, I suspect it is pretty easy to decipher which department is which if one really wants to find out.

Table 1: New Tenure Track Faculty 2012-2019

Dept

 

# TT

 

A

 

9

 

B

 

4

 

C

 

3

 

D

 

2

 

E

 

4

 

F

 

3

 

G

 

4

 

H

 

4

 

I

 

2

 

J

 

2

 

K

 

1

 

L

 

1

 

 

In addition, I looked at data from our Office of Institutional Research, and found that all staffing (including secretaries, faculty and administration) in the CLAS is 79.8% white. Then looked at the demographics of the 12 departments that gained a tenure track faculty member.  Below in Figures 2a, b, c you can see the number of faculty/staff of color, overall department size, and percentage faculty/staff of color (or those who didn’t identify as white).

Table 2a: 2012 & 2019 Department Demographics

Department

 

A

 

B

 

C

 

D

 

 

 

# Faculty of Color

 

Dept
Size

 

% Faculty of Color

 

# FoC

 

Dept
Size

 

% FoC

 

# FoC

 

Dept
Size

 

% FoC

 

# FoC

 

Dept
Size

 

% FoC

 

FALL
2018

 

1

 

35

 

2.9%

 

7

 

22

 

31.8%

 

6

 

14

 

42.9%

 

2

 

13

 

15.4%

 

FALL
2012

 

4

 

42

 

9.5%

 

8

 

27

 

29.6%

 

4

 

12

 

33.3%

 

2

 

13

 

15.4%

 

 

Table 2b: 2012 & 2019 Department Demographics

Department

 

E

 

F

 

G

 

H

 

 

 

# Faculty of Color

 

Dept
Size

 

% Faculty of Color

 

# FoC 

 

Dept
Size

 

% FoC

 

# FoC 

 

Dept
Size

 

% FoC

 

# FoC 

 

Dept
Size

 

% FoC

 

FALL
2018

 

6

 

21

 

28.6%

 

1

 

8

 

12.5%

 

5

 

14

 

35.7%

 

2

 

19

 

10.5%

 

FALL
2012

 

4

 

14

 

28.6%

 

0

 

9

 

0.0%

 

3

 

11

 

27.3%

 

3

 

21

 

14.3%

 

 

Table 2c: 2012 & 2019 Department Demographics

Department

 

I

 

J

 

K

 

L

 

 

 

# Faculty of Color

 

Dept
Size

 

% Faculty of Color

 

# FoC 

 

Dept
Size

 

% FoC

 

# FoC

 

Dept
Size

 

% FoC

 

# FoC

 

Dept
Size

 

% FoC

 

FALL
2018

 

3

 

25

 

12.0%

 

3

 

17

 

17.6%

 

6

 

15

 

40.0%

 

1

 

13

 

7.7%

 

FALL
2012

 

3

 

26

 

11.5%

 

3

 

21

 

14.3%

 

7

 

20

 

35.0%

 

1

 

16

 

6.3%

 

 

From Table 1 it is clear that hiring is incredibly uneven. Department A gained 9 tenure track faculty in a 7-year period of time. 9 out of 39 new tenure track faculty in this period of time, or 23% of new faculty in the college joined Department A. In terms of diversifying the university, it can be argued that this department was given more opportunities to recruit faculty than any other department in our college. Yet, this department – which was not particularly diverse – actually became less diverse over time as seen in Table 2a.

At the same time, we also see departments that do not receive many (or any) lines are not likely to become diverse. For instance, Department L only had 1 hire/conversation. While this department is pretty homogenous, they have had far fewer opportunities to diversify. This may be obvious, but it is clear some departments have greater power to change than others.

While other departments received fewer new tenure track faculty, there are some interesting observations to be made. For instance, we can look at Department F, that had zero faculty of color and managed to recruit someone of color in one of their 3 searches/conversions.

Put another way, decisions made by Department A have wide ranging implications for faculty demographics. Blame might not be the right word, but they perhaps have a greater responsibility to think about the bigger picture. Departments that get lines, especially those that get repeat opportunities can dramatically change the campus climate for faculty of color. To put this into perspective, about 21.7% of our 479 faculty aren’t white. There were only 16 Black, 24 Latinx, and 48 Asian faculty members in Fall 2018. Given how low these numbers are, every new hire of a scholar of color is significant.  

How do we explain Department A?

I do think it is worth noting that, according to the 2017 Survey of Earned Doctorates, US citizens and permanent residents in his area of study are 79.3% white. This is also a field in which people do study communities of color and their culture. So, I have no doubt there are those who recognize the problem. This issue is likely due to 1) specific area of search and existing faculty interests 2) our geographic location 3) the way in which people are biased toward those that look the same, or come from similar backgrounds. The question, however, is whether people who realize there is a problem are willing to challenge the status quo, and be more creative in running searches. This also requires administration to help departments try new models of hiring. This is something other institutions have effectively done.

Consequences

There are a lot of consequences, but I want to focus primarily on university service such as involvement in the union. While large departments have downsides, a plus side is that workload can be spread out over more faculty. This includes department-level work, but also university-wide service. Politically, this can have consequences. Representation in our local union’s representative assembly is based on department size. In addition, large departments have an easier time having gaining additional representation through elected leaders in various “shared governance” bodies.

For existing faculty of color, this means more work. It is well documented that faculty of color do a lot of “invisible labor” through their service activities. Again, with so few black and Latinx faculty, individuals are repeatedly being ask to do more and more work.

In conclusion, I suspect if I were to look at data for other large departments in other colleges at my university, I may see something similar. Again, I would like to emphasize that large departments that receive lines have greater responsibility to the campus community to critically examine their search procedures.

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Reflections on Higher Ed during APAHM

So it is Asian Pacific American Heritage Month (APAHM). Increasingly, APAHM and annual events such as the Lunar New Year provoke odd feelings for me. As an Asian-American living in rural Pennsylvania and working in higher education, it can be awkward at times. In Berks County, where I live, the Asian (one race) population is 1.6%. On my campus less than 1% of students identify as Asian. A few years ago, I was asked at a conference if it was difficult being a faculty of color in rural Pennsylvania. I cannot say it has been horrible, but it is certainly awkward.

Being Asian-American in higher education is complicated. Asians/Asian-Americans are considered “over-represented” in higher education relative to the general population. Even at my institution, 9.1% of faculty are Asian / Pacific Islander, while the Asian population in Pennsylvania is 3.6%. Yet, Asian-Americans are often forgotten as a minority group on and off campus.

Indeed, there is a rationale for the exclusion of Asian-Americans from the category of under-represented minority group(s). In 2015, there were 55,006 doctoral recipients in the United States. About 1/3 of degree recipients are temporary visa holders. Among the top countries origin for visa holders, China, India, South Korea, and Taiwan rank in the top 5 countries. Among U.S. citizens and permanent residents who received doctoral degrees, 8.7% were Asian-American – compared to 5.6% of the U.S. population. Of course, not all recipients of doctoral degrees work in universities. According to TIAA institute’s look at faculty diversity, 6.4% of all faculty are Asian-American and 2.1% of all faculty are immigrants (born and educated abroad). These two groups are also disproportionately at research institutions and not regional teaching-oriented ones such as my own.

However, this – and other – data tends to fuel the “Model Minority” myth and ignore the real experiences that people have. There are significant cultural and economic differences between different groups of Asian-Americans. The category of Asian includes people with heritage from about 4 dozen countries and many different ethnic groups. As such, the generalization of Asian-Americans as a single category is problematic. Moreover, income data that illustrates Asian-American success ignores the fact that Asian-Americans have the highest poverty rate in New York City, and there are high rates of poverty for many Southeast Asian groups. Asian-Americans are also faced with hate crimes and glass ceilings.

Just as the Asian-American category is problematic, Asian-American over-representation in higher education is not straightforward. It also does not mean an absence of racism, xenophobia, micro-aggressions, and various types of discrimination in the workplace. Take for example, in the life sciences 10.8% of recent PhDs are Asian-American versus the 4.3% in humanities fields. The resulting stereotype of Asians in STEM fields has consequences outside of those fields. For instance, there is a case of a political scientist profiled into teaching statistics. There are also concerns regarding the inclusion of Asian-American studies in curricula, and its consequences for tenure. The absence of the Chinese Exclusion Act and Japanese Internment from history lessons is revealing of the way in which Asian-Americans are still under-represented in higher education. At the same time, there is pressure for Asian-American scholars like myself – who do not work on Asia/Asian-Americans – to do so (stay tuned for a blog post on ‘mesearch’).

In conclusion, I cannot say it has been horrible, but it is certainly awkward.

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Fear of a black Spider-Man: racebending and the colour-line in superhero (re)casting

This paper tackles the way in which fans legitimise ‘whiteness’ in the pantheon of American fictional heroes. Using the 2010 internet meme calling for an African-American actor be cast as the next Spider-Man, and the replacement of Peter Parker with a character of Hispanic and African-American descent, I examine online arguments made by fans that Peter Parker and Spider-Man have been and therefore should remain white. Specifically, I am interested in the way in which fans legitimise the ‘casting’ choices of characters through the use of canon – the officially recognised history of a fictional universe – and dominant characterisations of Spider-Man as a hero.

(2015). “Fear of a black Spider-Man: racebending and the colour-line in superhero (re) casting.” Journal of Graphic Novels and Comics. DOI: 10.1080/21504857.2014.994647

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Teaching and Visualizing School Segregation: Google Docs

As I’ve discussed in an earlier post, education and race is a topic that I discuss in my classes. I’m also a big fan of providing visualized data for my students when I cover the material. So, I was very happy to see Reed Jordan at the The Urban Institute’s great post (with maps) on segregation in America’s public school system. Maps and other visual material support my lectures and PowerPoints in making the case that we are still very much a segregated country. Specifically, that this segregation is despite the country’s increased diversity. However, this post is not going to focus on segregation. Rather, I want to share the way I present information to my students via tables and charts in PowerPoint as well as Google Docs/Drive. Google Docs is not just a web-based replacement for Office. Part of Google Drive, it allows you to make Fusion tables to map and chart data. Its spreadsheet (and presentation program) can be embedded into webpages and other HTML files for easy online sharing (such as in your CMS). You can, of course, also share the spreadsheet if you wish.

Why do I want to share this material? If you’re a social scientist, you likely want to present data to your students. However, the charts included in publisher provided PowerPoints are ugly and often out-of-date.  I’m hoping that sharing my spreadsheets will help you to embedded figures, tables and charts into presentations and other course materials.

Source: http://nces.ed.gov/programs/digest/d13/tables/dt13_203.50.asp

As mentioned above, the segregation we see in American public schools is despite the country’s increased racial and ethnic diversity. For most kids in the United States, they are more likely to attend schools where other students look like them than otherwise. For instance, Orfield and Frankenberg’s report has notes that we are in an unprecedented era of diversity, but there has been a long retreat from integration. The question for me as an instructor is: how do I convincingly present evidence that contradicts students’ notions of societal progress – the idea that the present (and future) is better than that of the past.

I like to show my students several years of data (within their lifetimes) to suggest that the problem of segregation is long-standing and enduring. This is also when I remind my students that their parents were likely born in the 1960s (amidst the Civil Rights Movement). This means that the history of Jim Crow is not ancient history. In Figures 2 & 3, we see that there has not been a lot of change in the new millennium. 60 years after Brown v. Board, most White kids go to schools that are predominantly white, just as most African-American kids go to schools that are predominantly black, and Hispanic/Latino students go to schools with other Hispanic/Latino kids.

Embedded charts and figures from Google Docs are nice because they are somewhat interactive with mouse overs revealing numbers and other information. The option to export charts and figures as images is available as well. However, I like embedding the HTML. I also prefer inserting or creating charts and figures via Excel. This allows for easier updating and having the visualized data fit the theme of your website or PowerPoint (which I haven’t done here).

Source: http://nces.ed.gov/ccd/pubschuniv.asp

While differences remain, there is some good news. The number of high school dropouts has decreased, with the steepest decline being amongst Hispanic students. The mouse over effect is particularly useful in the line chart above and below.

Source: http://www.census.gov/hhes/school/data/cps/historical/index.html

The steep decline in dropouts parallels a record high of students aged 18- to 24-year-olds being enrolled in college. In fact, a greater percentage of Hispanic high school graduates were enrolled in college than Whites in 2012. However, differences remain. Including links to the data sources is important. When I teach my Sociology of Visual Culture class, I require students to get data from the U.S. Census bureau to use in their charts, figures, and tables.

Source: http://www.census.gov/hhes/school/data/cps/historical/index.html

 If this was a lecture, this is likely the point where I’d make a joke about information overload. I’ll wrap up by saying that I hope that my Google spreadsheet is useful (I hope to update it when I have more time). Also don’t forget, Reed Jordan’s post & maps on this issue. The maps are also embeddable.

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Prepping for Fall 2014: Visualizing School Closures

Splatter Compass

compassIn my previous post, I mentioned that I spend a lot of time during the summer prepping for academic year. This fall requires extra work because I’m changing textbooks, and re-organizing a lot of material. I’m not doing this just to improve the content or my teaching, but I do this to “exercise” my other skills – things like playing with Google Fusion Tables, Photoshop, HTML, etc.

This fall I’ll be teaching urban sociology again and I’m currently updating material for the course. New on the syllabus for this year is Robert Sampson’s book on Great American City: Chicago and the Enduring Neighborhood Effect. Reading the book the past few weeks inspired me to think of examples to help students make comparisons/connections between Chicago and Philadelphia.

Perhaps the most obvious example is that were both hit bad with school closures in 2013 affected whole communities.

Chicago Philadelphia
School Closings 2013 47 23
Students Displaced 12,700 10,000
Layoffs 2,000 3,700
Charter Schools opened 15 9

The Chicago Tribune has an excellent map that illustrates some of social and economic dimensions of neighborhoods affected by the closures. Since, I’m very much in favor of visualizing data for my statistics-adverse students, I’ve decided to make my own map in Google Fusion Tables to help me with my lesson plan in the fall. I can always use Social Explorer, but it’s also useful and fun for me go through the effort of downloading U.S. Census data and making my own map.

The below is a color coded map of census tracts based on the percent of those with high school diplomas or higher based. The purple flags are where the schools closed in 2013 are located.

[Click for Map w/ Race & Income]

In particular, the consequences for school closures have dramatically affected communities of color. The Root reports that while African-American Students represent 58% of the students in Philadelphia, they made up 81% of the students affected by the closures. In Chicago, black students account for 43% of all students, but 87 of those affected. In this map, I’ve set it up so that you can toggle layers to look at race, income, and education attainment, so that you can see the connection between race and school closures. Setting up the toggle was fun it required playing around with JavaScript. For more simple layered maps, I use the Fusion Tables Layer Wizard. However, I wanted to create something that was more interactive that students could play around with. This required trying to find a color scheme for the maps so that when you toggle layers, they interact with one another in a way that is visually informative.

I’ll continue to work on this throughout the summer, but I wanted to blog on how summer “prep” work isn’t just revising lectures and reading. It can be an opportunity to develop other skills.