Credit for the distinction of the worst MSNBC editorial ever goes to Julio Ricardo Varela, founder of Latino Rebels, for his 2 December column. Title: “The racism in this blue state can be illustrated with one infuriating statistic.” Subheading: “Latinos in Massachusetts face the greatest [sic: a greater] risk of winding up in foster care in Massachusetts than they do in any other state in the country.” Much of the column is a rehash of a Boston Globe article—its title equally ungrammatical—and a sustained grumble about public services affecting Latinos. Mr. Varela’s rehash fails in three ways: to identify that “one infuriating statistic,” to support his subtitle with comparative evidence, and to uphold his title’s allegation of racism. Aside from a paragraph mentioning antiracist “approaches” and “frameworks,” and “antiracism” training for “child welfare professionals,” he never discusses race.
I assume that the “one infuriating statistic” is the “overrepresentation” of Latino (not Latina or Latinx) children: the disparity between the percentages of Latino children in the state population (20%) and of Latino children in foster care (34%). Mr. Varela implies that it reflects the underrepresentation of Latino personnel in the DCF (16%). He thus insinuates that non-Latino DCF workers are biased against Latinos or ignorant of Latino culture and living conditions. Thus, they confuse the deprivations of poverty with parental negligence. But, if poverty were the primary factor, one would expect an even higher percentage of Latino children in foster care. For “The Latino poverty rate…is twice the state’s overall poverty rate.” If so, non-Latino DCF workers seem clear about the differences between the effects of poverty and the indications of neglect.
Without further analysis of “overrepresentation,” Mr. Varela sees the Boston Globe article on DCF problems and their effects on Latinos as “a reminder of the necessity of diversity, equity and inclusion (DEI) policies.” To him, “it seems obvious that a greater emphasis on diversity, equity and inclusion in hiring and in carrying out the agency’s mission would greatly benefit children stuck in a cycle of neglect, poverty and invisibility.” But this admission creates a contradiction between a confusing overlapping of neglect and poverty—“invisibility seems contrary to “overrepresentation”—and their separation here, and undermines his insinuation of DCF staff racism or ignorance. So he weakens his claim of “the necessity of diversity, equity and inclusion (DEI) policies.”
I am sure that as a founder of Latino Rebels, Mr. Varela is outraged, justifiably so, by the conditions in which many Latinos find themselves and the often callous treatment of many clients of government programs. But his anger which lashes out at agencies and their employees, especially with an insinuation of racism, is not constructive. Indeed, that insinuation is itself racist because it assumes that an individual’s race determines his or her attitudes, beliefs, conduct, and decisions. Ironically, Mr. Varela himself needs antiracism therapy.
Nothing about Mr. Varela’s column is helpful. But one feature commonplace among reformers of this or that social or educational cause merits attention. That commonplace is the assumption that any disparity in the distribution of populations by race, gender, religion, nationality or national origins, etc. is indicative of bias. Aside from the inherent bigotry of this commonplace, the major problem is that it discourages an analysis of the causes of the disparity, distracts from helpful remedies, and enables harmful results.
For example, one school board, distressed by the disparity in enrollments of White and Black students in AP classes, decided to eliminate the disparity by eliminating the classes. The result was that Black students who had worked especially hard to enroll in these classes were penalized because their percentages in the classes were not close to the percentage of Black students in the student body. No official explained how the decision benefitted highly qualified Black (not to mention White) students. Mr. Varela could have suggested a similar proportionality by proposing that DCF accept cases on the basis of quotas reflecting racial percentages of the population. Of course, many Latinos needing help would not get it, but, to him, disparities matter more than measures of benefit.
The commonplace terms which reflect an adverse opinion of such disparities are “overrepresentation” or “underrepresentation.” These are tricky terms because they imply some usually unstated standard for measuring representation. All too often that standard may be a biased one, which, if exposed, might enable a better analysis than the simple-minded comparison of numbers, percentages, or proportions.
Let me illustrate my point with a story from my consulting experience. The Director of the National Science Foundation (NSF) asked for my advice on a second NSF effort to develop a Congressionally mandated annual report on minorities and women in science and engineering. I asked for the first report to read as background for the second one. When we next met, I remarked that he must have had new carpets installed in his office since the first report. Surprised, he asked me why; I answered, to remove the blood shed in discussions about how to explain representation and, given the tacit bias of the task, underrepresentation. He smiled and admitted their intensity.
The data showed minorities and women overrepresented in the ”soft” sciences and underrepresented in the “hard” sciences. Likewise, the same data showed white men overrepresented in the “hard” sciences and underrepresented in the “soft” sciences. I pointed out that the standard for “underrepresentation for minorities and women was a white male standard. My advice: an introductory note about different meanings of “representation”: one, a presentation of data without any judgment about under- or overrepresentation; or two, the presentation of data according to a white-male-biased standard. Politics dictated a repeat: unexplained disparities in the distribution of race and gender populations in science and engineering as showing underrepresentation, to support Congressional concern about discrimination against minorities and women.
Notwithstanding that minorities and women are (still) discriminated against in science and engineering, no one knows that the end of discrimination would result in the end of disparities. More than racism and sexism may be factors. Male and female babies are born with slightly different propensities, which may explain their different aptitudes for, preferences for, and achievements in different fields.
My moral: statistics lie and lie only if we do not recognize their limitations. Statistics cannot tell what causes the distribution of people into certain lifestyles and careers. Or whether peoples’ choices which result in disparities by race or gender reflect innate differences, cultural biases, or social prejudices. Or whether racism or sexism is the cause of disparities. Or whether disparities should be eliminated. Statistics cannot identify problems; only the users of statistics can, because of pre-existing concerns. The problem with statistics is that the user, unaware of what he or she brings to their interpretation, can do harm as well as good. Consider statistics, yes; but be careful using them to support accusations of racism or sexism.
