That Paper About Hiring Chief Diversity Officers At Universities

That Paper About Hiring Chief Diversity Officers At Universities

The paper is “The Impact of Chief Diversity Officers on Diverse Faculty Hiring” by Steven W. Bradley, James R. Garven, Wilson W. Law, and James E. West. (Thanks to John Cook for the tip.) Here’s the abstract.

As the American college student population has become more diverse, the goal of hiring a more diverse faculty has received increased attention in higher education. A signal of institutional commitment to faculty diversity often includes the hiring of an executive level chief diversity officer (CDO). To examine the effects of a CDO in a broad panel data context, we combine unique data on the initial hiring of a CDO with publicly available faculty and administrator hiring data by race and ethnicity from 2001 to 2016 for four-year or higher U.S. universities categorized as Carnegie R1, R2, or M1 institutions with student populations of 4,000 or more. We are unable to find significant statistical evidence that preexisting growth in diversity for underrepresented racial/ethnic minority groups is affected by the hiring of an executive level diversity officer for new tenure and non-tenure track hires, faculty hired with tenure, or for university administrator hires.

Even accepting that, a finding which is confirmed by p-values and a model most complex, it cannot be said that hiring CDOs has had no influence. They have. At the very least, they have found new ways to spend millions upon millions of dollars, which contributes to tuition increases. They have created sensitivity training, which is more to less mandatory. They have created a climate (aha!) of suspicion. They enforce an official ideology. None of these are good things.

But did these CDOs manage to hire more non-whites professors than would have been hired in their absence? It is a counterfactual question whose answer must be yes. We have all seen cases where this is individually true: cronies here and there are found positions. The question the authors of the paper ask must be seen therefore as broader: was the relative increase in non-whites “large”, where large is defined by some model.

Now they say college presidents and provosts largely agree that “Most academic departments at my institution place a high value on diversity in the hiring process.” Meaning race counts. “Yet the number of new PhDs who are members of an underrepresented minority group vary widely by academic discipline.” How could this be? Rather, how could this be if the additional implicit premise of Equality is true?

I’ll skip over the various theories which tout “congruency”, which are the small but superior outcomes seen by non-white students taught by non-white professors. I’m sure some of this is true: people like to be with people who are like themselves.

The authors looked at large universities, where most data on race was voluntary. The U.S. Department of Education only recently mandated tracking and reporting by race. I wonder if they also subscribe to the ideology that race does not exist, that it is only a social construct? Never mind.

We are talking cause and effect: did hiring a CDO cause diversity, or did diversity (in students or faculty) cause the hiring of CDOs? Or are both true (at different places)? The authors used a model to answer this. “We found that decisions regarding a CDO at [Carnegie classification] R1 institutions within 100 miles do not have as much explanatory power over a R1 institution as the decisions regarding a CDO of all R1 institutions (excluding self) nationwide.”

A big problem with hypothesis testing is the rejection of truth. I bet it was true that at at least one place increased diversity caused (in part) the hiring of CDOs, and that at lease one other place hiring CDOs caused (in part) diversity. But a hypothesis-testing model (Bayesian or frequentist) rejects the “both true” possibility, and says only one can be truly true. And this is because, as you have often heard, probability models cannot identify cause. Think about this in the context of pills: the same pill may cure one man but sicken another, yet the model will reject one of these while claiming the other is the truly true.

Now the paper is large and intricate, so much so that it would bore us to go too deeply into it. We’ll do just the supposed cause-and-effect model, and only in brief.

“51 percent of respondent provosts from doctoral-granting public universities responded in the affirmative to the following question: ‘Either because of the protests, or because of prior/subsequent commitments, does your college currently have a target for increasing the number or percentage of minority faculty members you employ by a certain date?'”

Well, we all know colleges cannot withstand student “outrage”. A model is not needed.


“To better understand directions of causality, we implement a Granger Causality Test between the initial establishment of CDO and changes in student, faculty, and administrator hiring diversity, and growth in student applications for undergraduate admissions.”

Here is a picture of the model, where at university i “ΔU^f_it is the change in the proportion of underrepresented students from year t ? 1 to year t”, etc.:

Good grief! After that monstrosity came the p-values, and then exited the Briggs.

If only cause were so easy! No. You have to do the brutal hard work of going to each university and exploring it in depth, asking the people who did the hiring why they did the hiring, before and after their CDO, and try to tease out, for each hire, how much the effect or lack of the effect the CDO had on hiring whites or non-whites, and hope they aren’t misremembering, lying, or confused about how to answer. And who tells the truth on race anymore, given its acid effect on discussion?

Cause is hard! As it is, the model can give correlations, which are none too high, which only proves you again have to look university by university.


There are some gems in the paper, though. Such as the tacit admission “diverse candidates”, being in limited supply (they say), are sitting pretty. The term “diverse candidates” is also theirs. Golly.

We also learn that “Evidence points toward a congregation by field and subfield for underrepresented minorities.” Meaning there are few black economists and physicists new PhDs (2.6%), but there are many black education PhDs (27%). They say. See their Table 2 for a breakdown of American Indian, black, Hispanic, Asian, and white recent PhDs by field.

Blacks are 20% of “Area & Ethnic & Cultural & Gender Studies”, Hispanics 17.3%, Asians 9.5%, and whites 44.5%. Blacks are also high in “Public Administration” (25.2%). Blacks are lowest in “Foreign Languages and Literature” (0.8%) and “Geosciences & Atmospheric & Ocean Sciences” (1.2%).


  1. Sheri

    Blacks are less than 15% of the population. Any department with more than 15% black employees must replace them with other races based entirely on the percentage found in the US Census count. No more allowing blacks to cheat whites and others out of their 85%+ share of the positions. Same with women—never more than 51% of any department can be women.

  2. Gary

    Anybody interested in source data can check out The tools are clumsy but they work. You will have to search individual institutional websites for information about their CDOs.

  3. “I wonder if they also subscribe to the ideology that race does not exist, that it is only a social construct?”

    This is incoherent. If it doesn’t exist, then you can’t say that it “is” anything.

    If it is a social construct, or it is anything else, then it exists. Race is a category, and, like all categories, it is constructed by people to serve their purposes. Take “tall” and “short”. People created these words and decided how to apply them, using ever-shifting criteria. The ideas are social constructs. That doesn’t mean that the use of these categories is unrelated to physical properties. Height exists. But people are found with a continuum of heights. Societies decide that they would like to draw a fuzzy boundary separating the population into ?all and short segments.

    “If only cause were so easy!”

    This introduces a very good paragraph that more people should take to heart.

  4. Ray

    “If it is a social construct, or it is anything else, then it exists.”
    Like dragons and unicorns?

  5. “Like dragons and unicorns?”

    That is a good counter, thank you.

    I would say that race, etc. are categories that people make up that are based on observable characteristics and are applied to real things that exist, such as people. So it is incoherent to say that “race” doesn’t exist, because simply referring to it implies that it does, as a social construct. What people argue about is its significance: in what way are the individuals whom we place in different racial categories different, aside from the characteristics that form the basis of the classification.

    Unicorns exist as mythological creatures, but don’t exist in the way that horses exist (probably). They are objects that exist or not, apart from our opinions. But race, tallness and shortness, are categories by definition, so it makes no sense to say they don’t exist because they are categories.

  6. Kip Hansen

    Cmdr. Briggs ==> Like the new Home Page!

  7. Joy

    Rhinos are fat unicorns in their unpainted state.

Leave a Reply

Your email address will not be published. Required fields are marked *