Postethnic America? A Multicultural Training Camp for Americanists and Future EFL Teachers

Abstract

North American ethnic diversity—with its conflictive roots in the histories of migration, settlement, slavery and conquest—has always been what David Hollinger calls “a major preoccupation in American life” (101). According to Hollinger, the late twentieth century saw a considerable shift in the way this topic is discussed in the public sphere. He argues that while diversity generated little in the way of enthusiasm throughout the history of the United States, there is today a general consensus that it is a crucial and promising aspect of U.S. society (Chapter 4). In recent decades, he suggests, educators, employers, journalists, and politicians have come to embrace diversity as a “national value” (142). Hollinger’s stance toward this value, however, is ambivalent. While cherishing dissent as one of the core values of the multiculturalist stance, he argues for the necessity of containing what he sees as the excessively ethnocentric forces in the multicultural debate. Carefully evaluating the potentials and the pitfalls of what he calls the multicultural “doctrine”, Hollinger argues in favor of a multiplicity of malleable, epistemically unimportant identities. This multiplicity, he hopes, will help us to move away from unproductive dissent toward a pluralistic consensus—toward, that is, a “postethnic America”. Hollinger’s critique of multiculturalist excesses, echoed by scholars in the United States and in Germany, marks a decisive point in the public debate about the challenges of diversity for public education. Although the end of the twentieth century saw the demise of many affirmative action programs, it also witnessed a revitalized debate about the continuing, if altered, social significance and epistemic salience of politicized group membership in U.S. American postmodern society.KeywordsAmerican StudyLiterary TextForeign Language TeachingInterracial InteractionIntercultural LearningThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.