Category Archives: Education

A “Chilling” Study? Chill!

Education, Law, Politics, ,

Given the news media’s interest in surveys, a poorly-designed survey has the potential to spread a lot of misinformation. In late August, Dr. John Villasenor of UCLA surveyed 1500 college students’ understanding of and attitudes toward freedom of speech. He wrote up the results in an essay published by the Brookings Institution, explaining that the survey had not yet been subjected to peer review, but due to “the timeliness of the topic, I believe it is important to get some of the key results out in the public sphere immediately.”

The survey results were covered by several mainstream media, including CNN and the Wall Street Journal. They were summarized by Catherine Rampell of the Washington Post under the title “A chilling study shows how hostile college students are toward free speech.”

In his article, Dr. Villasenor reported five results of the survey.  Respondents were asked “Does the First Amendment protect ‘hate speech?’”  A plurality of 44% answered “no,” compared to 39% who said “yes,” and 16% who didn’t know. They were wrong, since the First Amendment protects offensive speech unless it is a threat or is directed toward producing imminent lawless action. Women were more likely than men to hold this incorrect belief.

Respondents were given the following hypothetical scenario.

A majority of students agreed, with Democrats being more likely than Republicans to condone shouting down a speaker.

They were also asked about the use of violence to silence a speaker.

The approval rate was much lower, but the fact that 19% approved of violence is certainly disconcerting. Men were more likely than women to condone violence.

Given the same scenario, respondents were asked whether “under the First Amendment, the on-campus organization sponsoring the event is legally required to ensure that the event includes not only the offensive speaker but also a speaker who presents an opposing view.” A majority (62%) incorrectly agreed that there was a legal requirement of balance.

Finally, respondents were given an item from a 2016 Gallup poll in which they were asked to choose between two types of university learning environments:

  • Option 1: Create a positive learning environment for all students by prohibiting certain speech or expression of viewpoints that are offensive or biased against certain groups of people.
  • Option 2: Create an open learning environment where students are exposed to all types of speech and viewpoints, even if it means allowing speech that is offensive or biased against certain groups of people.

A 53% majority chose the first option of prohibiting offensive speech, while 47% opted for the more open environment.

Shortly after the article was published, doubts about the validity of the survey were raised, with one critic labeling it “junk science.” It turns out that Dr. Villasenor is a professor of electrical engineering with no prior experience conducting surveys. His research was sponsored by the conservative Charles Koch Foundation. Of course, neither of these facts necessarily invalidates the survey.

A more important problem is that it is not clear how Dr. Villasenor obtained his sample. He does not claim that the survey was administered to a random sample of college students, but merely that the sample was “geographically diverse” and “approximately mirrors” the undergraduate population. This has led critics to conclude that he used a convenience sample of students who were available, but not necessarily representative of college students. Dr. Villasenor has acknowledged that this was an “opt-in” survey, a term used to refer to a survey using volunteers whose biases are unknown.

Dr. Villasenor further irritated survey experts by stating the confidence intervals, or the margin or error, around his results. This is inappropriate unless a random sample is used. (It should be noted that Dr. Villasenor covered his butt by saying that these confidence intervals were valid “to the extent” that his respondents were representative of college students, without actually claiming that they were representative.)

Dr. Villasenor also neglected to mention that his survey was conducted just a few days after the white supremacist rally in Charlottesville, VA, in which a peaceful demonstrator was killed. This violent incident may have temporarily reduced students’ tolerance for offensive speech.

Finally, it should be noted that in 2016, when Gallup asked a nationally representative sample of college students, carefully chosen using probability sampling, to choose between the two learning environments described above, 78% chose Option 2, the more open environment. While it is possible that student attitudes have changed dramatically in the past year, it is also possible that differences in sampling were responsible for the discrepancy.

Catherine Rampell defended Dr. Villasenor’s survey, correctly noting that no survey uses perfect random sampling in that sense that respondents are randomly chosen from a complete and accurate single list of all the college students in the country. However, her defense blurs the distinction between carefully conducted probability sampling and the apparently more haphazard methods used by Dr. Villasenor.

Sophia McClennen of Penn State has labeled Villasenor’s survey an example of “blue-baiting,” in which conservative organizations attempt to manufacture doubt about free speech protections on campus in order to undermine public confidence in higher education.  (This may be working.)

At the very least, the controversy suggests that journalists should be careful to determine that professional sampling techniques are used before reporting survey results.  On the other hand, some college students did give these responses, even if they came from a biased sample. This suggests that high schools and universities should devote more attention to educating students on the meaning and scope of the First Amendment.

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Republicans Say Colleges are Bad For the Country

Republicans Say Colleges Are Bad For the Country

Education, Politics, ,

We won with the poorly educated. I love the poorly educated.

Donald Trump (2/23/16)

Americans are used to the intense partisan divisions over many political issues—abortion, gun control, health care, economic policy, and so forth. However, education has largely escaped from partisan debate. Although Democrats and Republicans may squabble about how much money to spend on education, and how education is to be delivered, it has always been part of the conventional wisdom that education itself is valuable to the individual and the society. Thus it was surprising to read this headline from a new poll from the Pew Research Center: “Republicans increasingly say colleges have negative impact in U. S.”

The data come from a national survey of 2504 adults conducted June 8-18, 2017. Respondents were asked whether they thought each of five institutions—churches, banks, labor unions, the news media, and college and universities—have “a positive or negative effect on the way things are going in the country.” Here are the results comparing Republicans and Republican-leaners vs. Democrats and Democratic-leaners.

Although partisan differences of opinion on the value of labor unions and the news media were anticipated, differences in approval of colleges and universities were just as large. Moreover, partisan differences over the effects of colleges have increased sharply in the last two years. Here are the time trends.

The change is almost entirely attributable to Republicans. Although Democratic attitudes toward colleges have remained stable, Republican attitudes have shifted dramatically in the negative direction. As recently as 2015, 54% of Republicans said colleges had a positive impact on society and 37% said their impact was negative.

Furthermore, this negative shift among Republicans cannot be attributed exclusively to those who have not gone to college. Unlike their Democratic counterparts, Republican college graduates are slightly less likely to give colleges and universities positive ratings. This would seem to suggest that negative personal experiences may have played a role in their dissatisfaction.

The Pew survey is silent about the reasons for this change in opinion, so I guess I’m free to speculate. First of all, we should remember that there has been considerable partisan realignment in the last decade. Therefore, this result could be due as much to the migration of people who dislike colleges into the Republican Party as to attitude change toward colleges among people who were Republicans all along.

A second explanation may be the negative publicity colleges and universities have received due to excessive drinking (sometimes leading to deaths), increases in reported sexual assault, and attempts to censor campus speakers (although the public should be aware that most of the censorship takes place silently during the preparation of the guest list, rather than afterwards). However, much of the pushback against campus disciplinary action against accused rapists is coming from Republicans, and it is wealthy alumni that consistently oppose crackdowns on fraternities that encourage underage drinking. Therefore, some of the objections may be to the punishment of offenders rather than to the offenses themselves.

A third possibility is that Republicans are objecting to the knowledge produced by college and university faculty rather than campus social policies. Although Stephen Colbert may claim he was joking when he said that “Reality has a well-known liberal bias,” it is almost certainly true that more of the scholarship coming out of both the natural and social sciences contradicts Republican policies than supports them. This has generated well-organized and financed resistance from business interests, especially fossil fuel corporations whose future profitability is threatened by climate change. Although Shawn Otto gave his book,The War on Science, a nonpartisan title, the text makes it clear that the war is being waged by churches, business groups and Republican party operatives. Chris Mooney gave his similar book a more candid title: The Republican War on Science.

Regardless of the reasons for this attitude change among Republicans, it poses a threat to the continued funding of public colleges and universities. The university system in which I taught has seen a sharp drop in state funding over the past 30 years.

The middle and lower class young people for whom the State System of Higher Education (SSHE) was intended have largely been priced out of the market. Enrollment is dropping (for this and other reasons). A private consulting firm hired by the state of Pennsylvania—without student or faculty input—has recommended reorganization that will almost certainly involve cutbacks in programs and downsizing of the system. Meanwhile, SSHE has announced a 3.5% tuition increase for next year, as the system continues to circle the drain.

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Racialization and Student Athletes

The Stroking Community, Part 1

IUP’s Tuition Increase, Part 2

The Hidden Injuries of (the) Class(room)

Education, Social psychology,

This is the first of what I expect to be a series of posts on The Hidden Injuries of Class, named for the 1973 book of that title by Jonathan Cobb and Richard Sennett.

It is obvious that education is one of the primary institutions that reproduces social inequality; that is, it is one of the main reasons there is so little social mobility in the United States. Most commentators attribute this to two reasons.

The current research focuses on a third possibility—class differences that emerge from within the classroom. Since UMC children are more familiar with classroom norms, more “education-ready,” the classroom is not a level playing field, but rather one in which UMC children perform better while WC children appear more withdrawn and less intelligent. One classroom tradition that elicits these class differences in behavior asking students to raise their hands. Hand-raising introduces competition and social comparison into the classroom environment, which can be detrimental to the self-esteem of WC kids.

Sebastien Goudeau and Jean-Claude Croizet conducted three experiments with fith and sixth grade French school children. Children were divided into those with WC and UMC backgrounds according to the status of the parent with the highest occupational level. In the first study, 953 students responded to a reading comprehension test in which 15 questions were read and posted on a screen and the children wrote their answers is a notebook. The number of correct answers was scored. In a randomly determined half of the classes, students were instructed to raise their hands when they thought they knew the answer. In the other classes, this instruction was omitted.

The results showed that hand-raising interfered with the performance of the WC children but had no effect on the UMC kids.

In the other two experiments, the children’s actual social class was not a variable. Instead, the authors attempted to create a cultural advantage for half the children. The students performed a coding task in which they were asked to write down symbols that had been associated with certain letters. Half the students were given fifteen practice trials to become familiar with the coding task, while the others were given only five practice trials. Each class contained a mixture of students who were more or less familiar with the coding task.

As before, in half the classes, the kids were asked to raise their hands when they knew the answer, and in the other half, they were not. The results showed that hand-raising disrupted the performance of the students who were less familiar with the task, but had no effect on those more familiar with it.

Part of the reason social class differences are so discouraging to WC children is their hidden nature, which creates the illusion that there are real differences in ability between WC and UMC children. In the third study, all classes were instructed to raise their hands when they knew the answer, but an additional variable was introduced. Half of the classes were correctly informed that some students had had more opportunity to practice than others, while the other classes were not. When the students who were less familiar with the task were informed that others had this advantage, hand-raising no longer disrupted their performance.

Godeau and Croizet propose that UMC children enter school with more cultural capital than WC children. Parents provide their children with social capital when they teach them the skills and attitudes they need to succeed in school. Certain classroom practices, such as asking children to read aloud in front of the class, will serve to increase these differences. Asking teachers to avoid these activities is unlikely to be successful, and might deny WC kids an opportunity to overcome their deficits. More promising might be a preschool experience in which WC children are familiarized with educational culture. They should  be told often that their unfamiliarity with these behaviors does not mean that they are stupid.

You may also be interested in reading:

Racial Profiling in Preschool

Asian-American Achievement as a Self-Fulfilling Prophecy

The Stroking Community, Part 2

Education, Social psychology, ,

Please read The Stroking Community, Part 1 before continuing.

The Grading Leniency Assumption

The evidence for the bias assumption questions the validity of SETs, but it does not, by itself, explain grade inflation. The grading leniency assumption adds that college teachers try to obtain favorable evaluations by assigning higher grades and by reducing course workloads. Stroebe cites three surveys that show that a majority of faculty believe that higher grades and lower workloads result in higher SETs. One survey published in 1980 found that 38% of faculty respondents admitted lowering the difficulty level of their courses as a result of SETs. (I’m not aware of any more recent survey which asked this question, which is unfortunate.)

It should be noted, of course, that faculty may not be aware of having changed their behavior, or they may think they have done it for other reasons. One common reason given for watering down courses is that contemporary students are unprepared for college-level work. (One former colleague, for example, said, “You have to meet students at a place where they feel comfortable.” Unfortunately, that “place” gets closer to the downtown bars with each passing year.)

Indirect evidence for the grading leniency assumption comes from student behavior. Greenwald and Gillmore note that students would ordinarily be expected to report working harder in courses in which they expect to get a higher grade. However, in a study of over 500 classes, students reported doing less work in those courses in which they expected to get a higher grade, a finding which is readily explained by the grading leniency assumption.

Finally, there are studies of the effects of grades on future course enrollment. Some universities publish average grades by course and instructor at the university’s website, and it is possible to determine through computer signatures whether students have accessed this information. In two studies, consulting past grading data predicted future choices of courses and sections, with the sections with higher grades being preferred by about 2 to 1. In one of these studies, this preference for easier courses was greater among low ability students than high ability students.

It should be noted that lowering the students’ workload not only improves faculty evaluations, it also lowers the faculty’s own workload. There are fewer of those time-consuming term papers and essay exams to grade. Instead, teachers can give the multiple-choice exams that are considerately provided free of charge by the textbook publisher.

The faculty members with the most to lose in the current enviroment are those who attempt to maintain high academic standards and are punished for their integrity with low student evaluations. If they don’t have tenure, they could be fired. And even if they do have tenure, they are likely to be under considerable pressure from administrators to improve their evaluations.

Grade Inflation

Here’s another chart to remind you of how bad grade inflation has gotten. It shows the change over time in the frequency of letter grades.

Grade inflation is an unintended consequence of universities’ reliance on student evaluations. Can it be considered a good thing? Kohn proposes that grades serve three functions: sorting, motivation and feedback. If grades gradually lose their meaning, they become less useful as sorting criteria for employers and graduate schools and less useful as feedback to students. The students most harmed are the hard-working, high ability students who would have gotten A’s in the absence of grade inflation. They are no longer able to distinguish themselves from their more mediocre colleagues. Leading average students to believe they are doing better than they actually are could lead to unpleasant shocks after they graduate.

The motivational function of grading assumes that the rewards and punishments provided by grades induce students to work harder and learn more. But the picture that emerges from the course selection studies is one of students attempting to obtain higher grades without working for them. Stroebe suggests that grade inflation is most likely to demotivate high ability students, who might decide that studying is not worth the effort if they wind up with the same grades as their less deserving classmates.

It’s hard to see how grade inflation can be reversed. The Wellesley solution of mandating lower grades holds some promise, but only if it is adopted by almost all similar universities at about the same time, since if some universities attempt to control grade inflation while others do not, their students will be at a competitive disadvantage when applying for jobs or to graduate school. Princeton initiated a similar program, but abandoned it after peer colleges failed to follow suit. There was some concern that controlling grade inflation might cause studients not to come to Princeton.

A shorter-term solution is suggested by Greenwald and Gillmore. They propose that SETs be statistically corrected for the average grade in the class. Although their method is complicated, the gist of it is that if the distribution of grades in a class is lenient, SETs are reduced. If the distribution is strict, the instructor receives a bonus. Although this makes good sense to me, it’s hard to imagine a university faculty agreeing to it.

The implications of this research are depressing. Students and professors are rewarding one another for working less hard. They are caught in a social trap in which short-term positive reinforcement serves to maintain behavior that has long-term negative consequences for themselves, the university and the society. Meanwhile, colleges and universities, already under financial stress, are decaying from the inside out because they are failing to meet their most basic obligation—that of helping and requiring students to learn.

You may also be interested in reading:

The Stroking Community, Part 1

Asian-American Achievement as a Self-Fulfilling Prophecy

Racial Profiling in Preschool

The Stroking Community, Part 1

Education, Social psychology, ,

Grade inflation has been a fact of life at American universities for several decades. College grades are measured on a 4-point scale (A = 4, B = 3, C = 2, D = 1, F = 0). Since the 1980’s, grades at a large sample of colleges and universities, have increased on average by .10 to .15 points per decade. The overall grade point average now stands at about 3.15.

This would seem to imply that students have either gotten smarter or are working harder. However, verbal SAT scores of incoming students have declined sharply during this period, while math scores have remained relatively stable. There has also been a decline in the amount of time students report that they spend studying. On average, college students now claim to study only 12 to 14 hours per week. Assuming 16 hours of class time, that amounts to a work week of less than 30 hours.

More disturbing is the research of Richard Arum and Josipa Roksa. They administered the Collegiate Learning Assessment, a cognitive test measuring critical thinking, complex reasoning and writing, to 2300 students at 24 universities in their first semester and at the end of their sophomore year. They found only limited improvement (.18 of a standard deviation, on average), and no improvement at all among 45% of the students. Of the behaviors they measured, only time spent studying was associated with cognitive gains.

Beginning in the 1980s, colleges and universities entered what is sometimes called the “student-as-consumer” era. Almost all of them began routinely administering student evaluations of teaching (SETs), and basing decisions about tenure and promotion of faculty members in part on their SETs. Social psychologist Wolfgang Stroebe, in an article entitled “Why Good Teaching Evaluations May Reward Bad Teaching,” argues that SETs are responsible for some of the grade inflation. Stroebe has organized the research on SETs around two hypotheses which he calls the bias assumption and the grading leniency assumption.

The Bias Assumption

It has long been known that higher student grades are associated with better evaluations, both within and between classes. That is, within a class, the students with the highest grades give the instructor the most favorable evaluations. When you compare different classes, those with the highest average grades also have the highest average SETs. A recent meta-analysis found that grades account for about 10% of the variability in teaching evaluations.

Since these data are correlational, their meaning is ambiguous. They were initially interpreted to mean that teaching effectiveness influences both grades and evaluations. If so, SETs are a valid measure of instructional quality. Stroebe’s bias assumption states that students give favorable evaluations in appreciation for having less work to do and higher grades, and that this is an important source of bias which undermines the validity of SETs.

Over the years, this debate has been a source of animosity among college faculty. It is probably the case that SET believers receive more favorable evaluations than SET skeptics. SET believers sometimes accuse SET skeptics of making excuses for their poor student evaluations, while skeptics suggest that believers are in denial about the possibility that their high ratings are obtained in part by ingratiating their students.

The obvious—but unethical—way to test the bias hypothesis is to manipulate students’ grades in order to see what effect this has on SETs. Back in the days before ethical review of research with human subjects became routine, there were a few studies that temporarily gave students false feedback about their grades. They found that grades did affect evaluations. For example, in one study, students in two large sections of General Psychology taught by the same instructor were graded on slightly different scales. The instructor received better evaluations in the section with the more generous grading scale.

There are several other research findings that, while correlational, are consistent with the bias hypothesis.

  • In the early 2000s, Wellesley College, concerned about grade inflation, instituted a policy requiring that average grades in introductory course be no higher than 3.33. This resulted in an immediate decline in grades. Average SETs declined significantly in the affected courses and departments.
  • Greenwald and Gillmore found that the grade a student expected affected not only ratings of teaching effectiveness, but also had significant effects on logically irrelevant factors such as ratings of the instructor’s handwriting, the audibility of his or her voice, and the quality of the classroom. This suggests that there is a general halo effect surrounding lenient instructors.
  • The website Rate My Professors (RMP) contains 15 million ratings of 1.4 miliion professors at 7000 colleges. Professors are rated on easiness, helpfulness, clarity, “hotness” and overall quality. Easiness—a question that is seldom asked on institutional evaluations—is defined on the website as the ability to get a high grade without working hard. RMP ratings closely match the institutional SET scores of the same professors. The two dimensions most highly correlated with overall quality are easiness (r = .62) and hotness (r = .64). Obviously, the professor’s physical attractiveness is another threat to the validity of student evaluations that is deserving of study.

In my judgment, the best test of whether teachers with high evaluations are really better teachers are those studies which examine the effects of SETs in one course on performance in a followup course. For example, do students who give their Calculus I instructor a high rating do better in a Calculus II course taught by a different instructor? Stroebe found five studies using this research design. Three of them reported that those students who gave their instructors high SETs in the first course did more poorly in the followup course, one of them found no difference, and the fifth reported a mixture of negative and null effects depending on the item.

Merely finding no relationship between SETs in Course 1 and grades in Course 2 raises questions about the validity of SETs. The negative relationship found in the majority of these studies has a more radical implication. It implies that students learn less from those teachers to whom they give high evaluations. One of these studies found, however, that ratings of grading strictness in the first course were positively related to performance in the second.

Its important to noted that Stroebe does not claim that SETs are totally invalid as measures of teaching effectiveness, but only that they are strongly biased. Poor student evaluations can serve as a warning that faculty are not meeting their obligations. One recent study found a non-linear relationship between SETs and its measure of student learning. The students learned the most from professors whose SETs were near the middle of the distribution. They learned the least from those whose evaluations were the lowest and the highest.

There are a number of possible explanations for the bias hypothesis. One is simple reciprocity. When a professor does something nice for a student, the student returns the favor with a positive evaluation. SETs give students who are unhappy with their grades an opportunity to exact their revenge. A second explanation for the negative ratings given by students with lower grades is attributional bias. The self-serving attribution bias predicts that we maintain our self-esteem by taking personal credit for our successful behaviors but blaming our failures on external causes, such as poor teaching or unfair grading by the professor.

Please continue reading Part 2.

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The Stroking Community, Part 2

Asian-American Achievement as a Self-Fulfilling Prophecy

Racial Profiling in Preschool

Racial Profiling in Preschool

Education, Prejudice and discrimination, Social psychology, ,

Data from the U. S. Department of Justice, Office of Civil Rights, shows that African-American children, especially boys, are suspended or expelled from preschools at a higher rate than White children. For example, while 20% of preschool boys are Black, 45% of the boys suspended are Black. However, this is not proof of racial discrimination, since a skeptic could argue that, even at this young age, Black children are more likely to misbehave.

A new study by Walter Gilliam and his colleagues at the Yale University Child Study Center takes an experimental approach to this issue by holding the behavior of Black and White children constant and observing how teachers respond. Participants were 132 prechool teachers recruited at an annual conference. Sixty-seven percent of the teachers were White and 22% were Black. They took part in two studies.

In the first study, participants were shown a 6-minute video of four preschool children—a Black boy, a Black girl, a White boy and a White girl—seated around a table. The teachers were asked to watch for “challenging behavior,” but in fact the video did not contain any misbehavior. A computerized eye-tracking device was used to measure the amount of time the teachers spent watching each child. At the conclusion, the teachers were asked to report which of the four children required the most attention.

The eye tracking results showed that the participants spent more time looking at boys than girls, and more time looking at Black children than White children. In addition, the time spent gazing at the Black boy was significantly greater than would have been expected on the basis of his combined race and gender. The race of the teacher made no difference in this study.

The title of the paper frames the research as a study of implicit bias, and media reports of the study have followed suit. The authors define implicit bias as the “automatic and unconscious stereotypes that drive people to behave and make decisions in certain ways.” However, the teachers’ conscious appraisal of which child they paid the most attention to appeared to match the eye-tracking results fairly closely, as shown in the chart below. Apparently the teachers were well aware that they were paying more attention to the Black boy.

yale_implicit_bias_infographic_v07

I mention this because the term “implicit bias” is sometimes used to deny personal responsibility for one’s own and others’ discriminatory behavior on the grounds that it is unconscious. By labeling this as a study of implicit bias, the authors may have given their teacher-participants less blame for their behavior than they actually deserved.

In my title, I described these results as similar to racial profiling. Racial profiling targets people based on stereotypes about their race, as when the police stop and frisk Black teenagers having no evidence that they are committing crimes. Like the police, these teachers were scanning for misbehavior, and they responded by giving special attention to African-American boys. (An editorial writer for the New York Times drew this same analogy.)

These same participants also took part in a second experiment. In this study, they were asked to read a vignette describing a preschool child who repeatedly engaged in disruptive behavior. The child’s race and gender were manipulated by changing the child’s name (DeShawn, Jake, Latoya or Emily). Half the participants in each race and gender condition also read background information suggesting that the child lived with a single mother who was under a great deal of stress. The others were not given background information. The teachers were then asked to rate the severity of the child’s behavior and to recommend whether the child should be suspended or expelled.

The following results were found for ratings of the severity of the behavior.

  • The same behavior was rated as more seriously disruptive when the child was White than when he or she was Black.
  • Giving teachers background information increased the ratings of the severity of the behavior.
  • The Black teachers rated the behavior as more serious than the White teachers.
  • The background information increased the perceived severity of the behavior when the teacher was of a different race than the child, but the teachers responded more sympathetically to it when the teacher and the child were of the same race.

With regard to suspension or expulsion, the only finding was that Black teachers were more likely to recommend these options.

The results of the second study are not a good fit with the Department of Justice data, since the teachers appear to be discriminating against the White children. The researchers explain this by suggesting that these teachers expected the Black children to be disruptive, but held the White children to a higher standard. Therefore, the identical behavior was seen as more serious when attributed to a White child.

My guess is that had the same behavior been rated more disruptive when when the child was Black, the results would have been interpreted in a straightforward manner as discrimination against African-Americans. However, since the results were unexpected, a more complex explanation was presented. This explanation may be correct, of course. There is some evidence for “shifting standards” with respect to race. However, the authors could have strengthened their argument with a followup study measuring teachers’ expectations about the misbehavior of Black and White children and the extent to which the behavior described in their vignette violated those expectations.

Since the Black teachers were stricter overall, it appears that increasing the representation of Black teachers will not by itself reduce the number of suspensions and expulsions.

Some additional perspective on this issue is provided by a set of two experiments by Jason Okonofua and Jennifer Eberhardt. Their participants, grade school teachers, read a desription of either a White or Black boy in middle school who committed two infractions—one class disruption and one act of insubordination. After each incident, they were asked how severely the child should be disciplined.

There was no difference in the punishment recommended for Black and White boys after the first infraction. As shown in the table, the recommended disciplinary action increased in severity after the second infraction, but it did so more for the Black boy than for the White boy. (In the table, “feeling troubled” refers to a combined measure the the severity of the misbehavior and the extent to which it would hinder and irritate a teacher.)

Apparently, the teachers were more likely to infer a disposition to misbehave from two bad actions when the child was African-American than when he was White.

You may also be interested in reading:

White Prejudice Affects Black Death Rates

Outrage

Asian-American Achievement as a Self-Fulfilling Prophecy

Racialization and “Student-Athletes”

Education, Politics, Prejudice and discrimination,

The spillover of racialization hypothesis proposes that white racial attitudes are significant predictors of their opinions about a variety of race-neutral social policies. For example, Martin Gilens found a strong relationship among whites between anti-black prejudice and opposition to welfare, which was explained by the fact that whites greatly overestimated the percentage of welfare benefits going to African-Americans. Racialization has increased during during Barack Obama’s presidency. Michael Tesler found that racial attitudes have become a stronger predictor of attitudes toward health care reform in recent years. In addition, attitudes toward two specific health care plans were more strongly affected by prejudice when the plans were attributed to Obama than when they were attributed to Bill Clinton.

It is difficult to reconcile the conflicting estimates of the amount of money generated by college sports, but the National Collegiate Athletic Association (NCAA) reports revenue approaching $1 billion per year. In 2013, the University of Texas athletic program alone generated $166 million, and 13 universities took in over $100 million. The NCAA will receive $7.3 billion to broadcast the College Football Playoffs between 2014 and 2026, and $11 billion for the NCAA Basketball Tournament for 14 years.

On the other hand, the college students who play in these games, whose labor is at least the equivalent of a full-time job, and who risk permanent injury, are only permitted to receive athletic scholarships that cover tuition, books, fees, room and board. Preventing athletes from receiving compensation while everyone else profits so greatly has to qualify as one of the great economic injustices of our time. Yet a 2015 HBO Real Sports/Marist poll found that 65% of Americans are opposed to paying college athletes for their labor.

There are a number of possible explanations for this result. It could be partly a matter of self-interest, since people might reasonably infer that ticket prices, cable television fees and college tuition will increase if the athletes are paid. However, most people, when asked about student athletes, probably think of college football and basketball, and since the majority of college football and basketball players are African-Americans, racial attitudes may also be relevant. In fact, the HBO poll found that 55% of African-Americans favor paying college athletes, compared to 42% of Latinos and only 26% of whites.

This led economist Kevin Wallsten and his colleagues to look into the possible racialization of this issue. (This post is based not on their journal article, which is as yet unpublished, but on an article they wrote about it for the Washington Post.) With the help of the Cooperative Congressional Election Study, they conducted a survey in which respondents were asked about paying student athletes and also completed a measure of “racial resentment,” two items from the Modern Racism Scale. In a statistical analysis that controlled for other influences, they found that racial resentment was the most significant predictor of white opposition to pay-for-play.

Nevertheless, these data are correlational. It’s possible that some other variable associated with racial resentment is responsible for this outcome. Therefore, they did a followup experiment in which they manipulated the salience of race prior to asking about paying student athletes. They did this by showing one group pictures of young African-American men identified as student athletes prior to asking the question, while another group was not shown any pictures. This is a priming manipulation, similar to Tesler’s experiment in which he attributed health care plans to either Obama or Bill Clinton. The results are shown below.

Both among all whites, and the subset identified as most racially resentful, opposition to paying college athletes was greater following the priming of race. That is, merely inducing the participants to “think about” black people, either consciously or unconsciously, reduced support for the policy.  While race may not be the only factor affecting attitudes toward pay-for-play, these results clearly imply that it plays a causal role.

It reminds me of a study in which whites were more in favor of voter I. D. laws when primed with a picture of black people voting than when the voters in the photo were white. We seem to be in a historical period in which attitudes toward most domestic political issues, as well as party affiliation, are affected by racialization. Many white people oppose social policies if they believe, rightly or wrongly, that the policies primarily benefit blacks, although they may not be aware that this is the reason for their opposition and would probably deny it.

The myth of the “student-athlete” is one of the most embarassing hypocrisies in higher education today. Since most of those who control decisions about possible payment are white, it’s hard to be optimistic about obtaining justice for college athletes through any mechanism other than the courts.

You may also be interested in reading:

A Darker Side of Politics

Guarding the Hen House

Voter I. D. and Race, Part 1

Asian-American Achievement as a Self-Fulfilling Prophecy

Education, Social psychology,

Most discussions of self-fulfilling prophecies are about the harmful effects of negative stereotypes. We are all aware, for example, of the tragic consequences of the belief by police that young black men are more violent than other young men. But stereotypes can be positive as well as negative.

Two sociologists, Drs. Jennifer Lee and Min Zhou, propose that positive stereotypes can become self-fulfilling prophecies that boost the academic achievement of Asian-American children. For their book, The Asian American Achievement Paradox, they interviewed 140 adult children of Chinese, Vietnamese and Mexican immigrants, and surveyed 4780 second generation immigrants. (This post is based on an article by Dr. Lee about their findings.)

A self-fulfilling prophecy is a behavioral sequence in which an initially false definition of a situation elicits behavior which causes the false expectation to be confirmed. The effects of self-fulfilling prophecies on classroom teachers was originally demonstrated in a 1968 experiment by Rosenthal and Jacobson in which teachers were told that a randomly-selected 20% of their incoming students showed unusual potential for academic growth. The researchers manipulated a positive expectation, since it would have been unethical to manipulate a negative one. In this segment from an old instructional video, Robert Rosenthal discusses his studies of teacher expectancy effects. The narrator is Phil Zimbardo.

A successful self-fulfilling prophecy involves five steps. In what follows, I’ll use the terms perceiver to refer to the person who forms the expectation, in this case, a teacher or guidance counselor, and target to refer to the person about whom the prediction is made, in this case, an Asian-American student.

  1. The perceiver forms an expectation. Based on previous experience or hearsay, the perceiver comes to believe that most Asian-American children are intelligent.
  1. The perceiver acts on the basis of that expectation. The target receives favorable treatment. He or she may be given more opportunities to perform well, or more informative feedback. Dr. Lee cites examples of Asian-American students with mediocre records who were surprised to be assigned to advanced placement courses.
  1. The target responds to the perceiver’s behavior. Dr. Lee reports that the majority of Asian-American students responded to these better opportunities and increased competion by performing well. Thus, the teachers’ expectations received behavioral confirmation.
  1. The perceiver interprets the target’s responds. “Aha!” they say, “I was right. Asian students really are smart.” Teachers typically overlook the role that their own behavior played in confirming their expectations.
  1. The target interprets his or her own actions. The Asian-American students observe their own performance and they also conclude that they are intelligent. This is the ultimate irony of the self-fulfilling prophecy. Targets wind up attributing to themselves the very qualities that the perceiver erroneously expected.

This seems like a benign outcome. But the researchers also interviewed Mexican-American children and observed the opposite side of the coin. Only 86% of their Mexican-American students graduated from high school, and a mere 17% graduated from college. If you work through the above five steps substituting a negative stereotype of Mexican-American children, you’ll see how self-fulfilling prophecies can contribute to a vicious cycle of prejudice and discrimination.

Of course, you can’t prove that self-fulfilling prophecies play a causal role in the achievement of Asian-American children just by doing interviews or surveys. However, Lee and Zhou’s claims are credible in light of past research.

The authors are not suggesting that self-fulfilling prophecies are the only reason for high achievement among Asian-American children. They also attribute their success to the cultural values of their parents, enhanced by U.S. immigration policies which gave preference to more highly educated Asians.

Dr. Lee also points out that the minority of Asian-American students who are unable to meet their parents’ and teachers’ high expectations suffer from lower self-esteem than they would have had they not been expected to do well. Also on the negative side, the stereotype that Asians are better followers than leaders may impose a “bamboo ceiling” on Asian-American advancement in the business world, which may explain why they are underrepresented among CEOs.