Discrimination

Is The Motherhood Penalty Real? The Evidence From Poland

It has long been assumed that the residual gap in earnings between men and women (after controlling for productivity characteristics, occupation and industry segregation, and union membership status) is due to gender discrimination. A growing body of evidence, however, suggests that it may also reflect the effect of having children.

According to this research, employed mothers now account for most of the gender gap in wages (Glass 2004). In the U.S., controlling for work experience, hourly wages of mothers are approximately four percent lower for each child they have, compared to the wages of non-mothers (Budig and England, 2001). The magnitude of these family effects differs across countries, but, in general, men accrue modest earnings premiums for fatherhood, whereas women incur significant earnings penalties for motherhood (Waldfogel, 1998; Harkness and Waldfogel, 2003; Sigle-Rushton and Waldfogel, 2007; Budig and Hodges, 2010; Hodges and Budig, 2010; Smith Koslowski, 2011).

The size of the penalty seems also to vary by whether women and men are toward the top or bottom of the employment hierarchies of skills and wages, and it also varies across countries (England et al. 2014; Cooke 2014). The findings in this area are sometimes inconsistent, however, and suggest that there is a need to include a combination of skills and wages (England et al. 2014) and to choose carefully measures of job interruptions (Staff and Mortimer, 2012).

Not All Discipline Disparities May Be The Result Of Implicit Bias

Over the past few months, we have heard a lot about discipline disparities by race/ethnicity and gender -- disparities that begin in the earliest years of schooling. According to the Civil Rights Data Collection Project by the U.S. Department of Education's Office for Civil Rights, "black students represent 18% of preschool enrollment, but 42% of preschool students suspended once and 48% of students suspended more than once." It also found that "boys receive more than three out of four out-of-school preschool suspensions."

This focus on student discipline disparities has also drawn attention to the research on implicit bias -- the idea that we all harbor unconscious attitudes that tend to favor individuals from some groups (whites, males, those judged to be good looking, etc.), and that disadvantage people from other groups (people of color, women, ethnic minorities, etc.). The concept of implicit bias suggests that good or bad behavior is often in the eye of the beholder, and disparities in disciplinary outcomes (e.g., suspensions and expulsions) may be influenced by unconscious stereotypes.

Part of me is very glad that we are finally having this conversation. Acknowledging the existence and consequences of subtle, implicit forms of prejudice is an important and necessary first step toward mitigating their effects and advancing toward fairness -- see my implicit bias series here. But it sometimes seems that the discipline and the implicit bias conversations are one and the same, and this concerns me for two reasons.

What Is Implicit Bias, And How Might It Affect Teachers And Students? (Part II - Solutions)

This is the second in a series of three posts about implicit bias. Here are the first and third parts.

In my first post on this topic, I argued that teachers are better positioned than, say, doctors or judges, to learn specifics about the individuals they serve. This strategy – called “individuating” – has proven to be effective in reducing implicit biases (related to race, gender, ethnicity, etc.). This post offers additional thoughts on how we might support teachers' orientation to get to know their students. Second, I discuss additional strategies that have been proven to be effective in mitigating the effects of implicit biases.

A couple of weeks ago, a colleague asked a great question during the Shanker Institute’s Good Schools Seminar on "Creating Safe and Supportive Schools." His question was motivated by a presentation on implicit bias by Kirwan Institute director Sharon Davies. The question was: Wouldn’t you expect more conscious, systematic decision-making (and fewer automatic, snap judgments) from teachers who, after all, see their students everyday and get to know them well? (See here, minute 50:55.)

As I related in the previous post, individuating (or learning about the particulars of a person, his/her interests, skills, family, etc.) can be a very effective "de-biasing" tool.* So, how might we leverage and support teachers' natural inclination to get to know students well? How might a potential de-biasing intervention build on this feature of teachers' work?

What Is Implicit Bias, And How Might It Affect Teachers And Students? (Part I)

This is the first in a series of three posts about implicit bias. Here are the second and third parts.

The research on implicit bias both fascinates and disturbs people. It’s pretty cool to realize that many everyday mental processes happen so quickly as to be imperceptible. But the fact that they are so automatic, and therefore outside of our conscious control, can be harder to stomach.

In other words, the invisible mental shortcuts that allow us to function can be quite problematic – and a real barrier to social equality and fairness – in contexts where careful thinking and decision-making are necessary. Accumulating evidence reveals that “implicit biases” are linked to discriminatory outcomes ranging from the seemingly mundane, such as poorer quality interactions, to the highly consequential, such as constrained employment opportunities and a decreased likelihood of receiving life-saving emergency medical treatments.

Two excellent questions about implicit bias came up during our last Good Schools Seminar on "Creating Safe and Supportive Schools."

Mind The Gap

We have been engaged in decades-long public policy debates on gaps and how best to close them: the income gap, the student achievement gap, gender-linked gaps in employment opportunities. But why do we care so much about gaps? In a land of diversity, why are subgroup differences such a concern?

At a basic level, we care about gaps because (or when) our fundamental assumption is that, on a “level playing field," there should be no systematic differences among people based on ascribed traits, such as race and gender, that are unrelated to the “game." It is “ok” if a specific Hispanic kid performs at a lower level than his/her white counterpart or vice-versa. But it’s not ok if, on average, Hispanic students’ test scores systematically lag behind that of similar white children. Why? Because we know intelligence and ability are normally distributed across racial/ethnic groups. So, when groups differ in important outcomes, we know that this "distance” is indicative of other problems.

What problems exactly? That is a more complex question.

Gender Pay Gaps And Educational Achievement Gaps

There is currently an ongoing rhetorical war of sorts over the gender wage gap. One “side” makes the common argument that women earn around 75 cents on the male dollar (see here, for example).

Others assert that the gender gap is a myth, or that it is so small as to be unimportant.

Often, these types of exchanges are enough to exasperate the casual observer, and inspire claims such as “statistics can be made to say anything." In truth, however, the controversy over the gender gap is a good example of how descriptive statistics, by themselves, say nothing. What matters is how they’re interpreted.

Moreover, the manner in which one must interpret various statistics on the gender gap applies almost perfectly to the achievement gaps that are so often mentioned in education debates.

Rethinking Affirmative Action

Affirmative action has been defined as "voluntary and mandatory efforts undertaken by federal, state, and local governments, private employers and schools to combat discrimination, foster fair hiring and advancement of qualified individuals regardless of their race, ethnicity and gender; and to promote equal opportunity in education and employment for all." It is also a highly controversial policy, with few fans and many detractors.

Some of this is due to the history of expedient implementation, where affirmative action came to mean a ham-handed system of quotas. But much of the unease is due to disagreement with the policy’s intent.

Many conservatives argue that fairness requires that we do away with preferences and treat everyone exactly the same way. Meanwhile, some liberals criticize nondiscrimination statutes for their focus on race, religion, and gender to the exclusion of socioeconomic factors that can be more limiting. How, they argue, could you consider the son of an African-American neurosurgeon to be more disadvantaged than the son of an illiterate white sharecropper?  It’s a very good question.

In Performance Evaluations, Subjectivity Is Not Random

Employment policies associated with unions – e.g., seniority, salary schedules – are frequently criticized for not placing the highest premium on performance. Detractors also argue that such policies, originally designed to protect workers against discrimination (by gender, race, etc.), are no longer necessary now that federal laws are in place. Accordingly, those seeking to limit collective bargaining among teachers have proposed that current policies be replaced by “performance-based” evaluations – or at least a system that would make it easier to reward and punish based on performance.

Be careful, argues Samuel A. Culbert in a recent New York Times article, “Why Your Boss is Wrong About You." Culbert warns that there are serious risks to deregulating the employment relationship, and leaving it even partially in the hands of the employer and his/her performance review:

Now, maybe your boss is all-knowing. But I’ve never seen one that was. In a self-interested world, where imperfect people are judging other imperfect people, anybody reviewing somebody else’s performance ... is subjective.

This viewpoint may sound obvious, but social science research reminds us that the whims of subjective human judgment are not random. The inefficiencies that Culbert mentions are inevitable, but so is the fact that bias tends to operate in a manner that disproportionately affects workers from traditionally disadvantaged social groups, such as women and African Americans. What’s worse – it’s just as likely to occur within as between groups, and we often do it without realizing.