The Color of Law: A Forgotten History of How Our Government Segregated America

Richard Rothstein

New York Times Bestseller • Notable Book of the Year • Editors' Choice Selection One of Bill Gates’ “Amazing Books” of the Year One of Publishers Weekly’s 10 Best Books of the Year Longlisted for the National Book Award for Nonfiction An NPR Best Book of the Year Winner of the Hillman Prize for Nonfiction Gold Winner • California Book Award (Nonfiction) Finalist • Los Angeles Times Book Prize (History) Finalist • Brooklyn Public Library Literary Prize This “powerful and disturbing history” exposes how American governments deliberately imposed racial segregation on metropolitan areas nationwide (New York Times Book Review). Widely heralded as a “masterful” (Washington Post) and “essential” (Slate) history of the modern American metropolis, Richard Rothstein’s The Color of Law offers “the most forceful argument ever published on how federal, state, and local governments gave rise to and reinforced neighborhood segregation” (William Julius Wilson).

Race & EthnicityRace & Ethnicity · medium confidenceRace & Ethnicity81 signalsLlm Classifier: Race & Ethnicity -> Race & EthnicityGoogle Books: Social Science -> Society & CultureKeyword Classifier: American History -> American HistoryCivil Rights & Racial JusticeBlack History & CultureImmigration, Refugees & Borderlands
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies

This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.

  1. 01 Central figures

    None extracted with sufficient confidence.

  2. 02 Central places

    None extracted with sufficient confidence.

  3. 03 Suggested argument

    Rothstein argues that federal, state, and local governments deliberately imposed and reinforced neighborhood segregation in America’s metropolitan areas.

    Model confidence 78%

  4. 04 Reading orientation

    35 / 100 academic

    Serious trade

    An estimate of intended readership and scholarly apparatus—not quality or importance.

Confidence percentages are the model's own estimates. Profile confidence: 60%.