Mixed Race Studies

Genetic Determinism, Technology Optimism, and Race

The ANNALS of the American Academy of Political and Social Science
Volume 661, Issue 1, 2015
pages 160-180
DOI: 10.1177/0002716215587875

Jennifer Hochschild, Henry LaBarre Jayne Professor of Government; Professor of African and African American Studies
Harvard University

Maya Sen, Assistant Professor of Public Policy
Harvard University

We begin with a typology of Americans’ understanding of the links between genetic inheritance and racial or ethnic groups. The typology has two dimensions: one running from genetic determinism to social construction, and the other from technology optimism to technology pessimism. Construing each dimension as a dichotomy enables four distinct political perspectives on the possibilities for reducing racial inequality in the United States through genomics. We then use a new public opinion survey to analyze Americans’ use of the typology. Survey respondents who perceive that some phenotypes are more prevalent in one group than another due to genetic factors are disproportionately technology optimists. Republicans and Democrats are equally likely to hold that set of views, as are self-identified blacks, whites, and Latinos. The article discusses the findings and speculates about alternative interpretations of the fact that partisanship and group identity do not differentiate Americans in their views of the links between genetic inheritance and racial inequality.

Read the entire article here.

Researchers have been thinking about race all wrong

Vox
2014-12-15

Jenée Desmond-Harris

Studies on race are a dime a dozen: researchers examine its relationship to everything from elementary school test scores to who’s most likely to develop diabetes to which groups are overrepresented in ethnic militias to who Americans vote for, and we read about the results in news stories that are supposed to help us makes sense of the world.

But two Ivy League scholars say race is actually much more complicated than decades of social science research has acknowledged, and they’re working to change that.

In their paper, “Race a Bundle of Sticks: Designs that Estimate Effects of Seemingly Immutable Characteristics,” which will be published in the Annual Review of Political Science, Harvard’s Maya Sen and Princeton’s Omar Wasow explain that people who do quantitative research on race typically treat it as a single, fixed trait — what scientists call an “immutable characteristic.”

Instead, they argue, quantitative researchers should acknowledge that any one person’s racial identity is more like a collection of many different factors — from skin color, to neighborhood, to language, to socioeconomic status. With this insight, it becomes possible to study race not as a single, unchanging variable, but rather as a “a bundle of sticks” that can be pulled apart and carefully examined one by one…

Read the entire article here.

Race as a ‘Bundle of Sticks’: Designs that Estimate Effects of Seemingly Immutable Characteristics

Annual Review of Political Science
Number 19 (2016)
2014-10-05
49 pages

Maya Sen, Assistant Professor
Harvard Kennedy School
Harvard University

Omar Wasow, Assistant Professor
Department of Politics
Princeton University

Although understanding the role of race, ethnicity, and identity is central to political science, methodological debates persist about whether it is possible to estimate the effect of something “immutable.” At the heart of the debate is an older theoretical question: is race best understood under an essentialist or constructivist framework? In contrast to the “immutable characteristics” or essentialist approach, we argue that race should be operationalized as a “bundle of sticks” that can be disaggregated into elements. With elements of race, causal claims may be possible using two designs: (1) studies that measure the effect of exposure to a racial cue and (2) studies that exploit within-group variation to measure the effect of some manipulable element. These designs can reconcile scholarship on race and causation and offer a clear framework for future research.

Read an advanced copy of the entire article here.