Smith College Protests: Beneath Outrage, Statistical Confusion

Two leaked letters between staff and administrators at the Smith College School for Social Work have led to mass student protests of perceived institutional racism.

Professors alleged that admissions staff were doing a disservice–particularly to minority students–by admitting unprepared students to the program, despite “overwhelming data that demonstrates that many…students, including white­-identified students, cannot offer clients a social work intervention that is based upon competence, skills and ethics.”

The unnamed source of the leak, as well as students, took umbrage over some of the terminology and implications of the letters, citing “violent, racist rhetoric.”

Protests at Smith College are somewhat of a perennial occurrence, but this case is particularly interesting because it deals in part with matters that can be verified through existing data. Moreover, arguments from the students present good opportunities to debunk common fallacious assumptions and underscore the importance of viewing statistics in proper context.

The first such assumption is that members of differing groups should be expected to achieve similar results and outside factors are to blame when this isn’t the case.

Contemporary politics are inundated with references to various forms of inequality. Why would we expect that there would be huge differences across people of varying (ethnic) groups except when it comes to academic performance? Indeed, racial achievement gaps are a widely acknowledged phenomenon.

For this reason, student Chris Watkins’ statement that a “disproportionate amount of black and Latino students” are under review, which can endanger their chances of graduation, isn’t enough to indicate racism. There’s no reason to assume that black and Latin students as a group would do as well as whites or Asians besides that we might find it ideologically appealing.

The second assumption is that multivariate groups of people can be divided neatly by single variables. Speaking of black, Latino, and white students assumes that the students that fall into these categories share all other variables that might affect educational performance.

Students could just as easily be separated by family income or some other variable that correlates to academic success. We wouldn’t expect black students from poor, single-parent households and upper class black students whose parents are Ivy League alumni to succeed at the same rates, even though both are black. Any discussion of racial outcomes that doesn’t take other factors into account is too blunt to deserve much weight.

Even if racism were a factor in determining which students are put on review, as Watkins seems to allege, the proportion of students on review by race wouldn’t tell us that, which brings me to my third point: Gross statistics are easily digestible, but can rarely be trusted to convey the nuances of a situation. Discrimination could be inferred statistically, but Watkins is looking in the wrong place for evidence.

In 1991 the Federal Reserve Bank of Boston found that after adjusting for several factors, blacks loan applicants were rejected about 17% of the time, compared with 11% for white applicants. The Boston FED felt that this was enough to infer racial discrimination on the part of lenders, which confirmed an existing belief held by the researcher.

It was only later that a writer at Forbes pointed out that racial discrimination would be evidenced not in the percentage of rejected applicants, but in the default rates of the borrowers. Lower rates of default among black borrowers would indicate that their applications were being held to tighter standards than comparable white applications. Since black and white default rates were even, it appeared that race was not a deciding factor in the lenders’ decision-making process.

We can apply the same logic to this accusation of faculty racism at Smith College. It’s not enough to demonstrate that a higher proportion of black and Latino students are placed under review; we need to know they’re outperforming white students who are also placed on review, or inversely, if among students not under review whites had a lower GPA than black and Latino students.

Similarly, we can evaluate the complaints of Professor Dennis Miehls and the “Concerned Adjuncts.”

If, as the letters from staff seem to imply, unqualified students were being admitted because of an administrative predilection for non-academic qualities,[1] we would probably find some evidence of that in the incoming GPAs (or other metric of gauging academic preparedness) of students under review relative to their successful peers. Since the Smith College MSW program doesn’t require applicants to take a GRE, work experience, undergraduate GPA, and SAT scores might be the best such indicators.

In a school so often embattled by protests and accusations of racism, students and faculty should take this chance to quantitatively assess whether or not racism is affecting the performance of minority students on campus. With any luck, someone with access to the right data will perform a competent analysis.

[1] It would hardly be the first time a university admitted based on preferential characteristics that had nothing to do with academic success. Among students admitted to medical schools between 2013 and 2016, black and Latino students have lower median GPAs and MCAT scores than white applicants, who are similarly behind Asian applicants. Among applicants with comparable MCAT and GPAs, black and Latino students are far more likely to be accepted, indicating an admissions preference.

 

Advertisements

One thought on “Smith College Protests: Beneath Outrage, Statistical Confusion

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s