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001 on1519459354;

003 OCoLC;

005 20260227142359.9;

007 ta;

008 250514t20262026nyua b 001 0 eng d;

019 a| 1519447224;

020 a| 9780231213639;

020 a| 023121362Xq| (hardcover);

020 a| 9780231213622q| (hardcover);

020 a| 0231213638q| (paperback);

020 z| 9780231559942q| ePub ebook;

035 a| (OCoLC)1519459354z| (OCoLC)1519447224;

050 4 a| HN90.S6b| K38 2026;

082 04 a| 305.82| 23;

084 a| 71.62b| cl;

100 1 a| Kaufman, Jay S.,d| 1963-e| author.1| https://id.oclc.org/worldcat/entity/E39PBJdmgbfc3gqRkXg6Tyd4v3=| ^A1329520;

245 14 a| The race variable :b| how statistical practices reinforce inequality /c| Jay S. Kaufman.;

264 1 a| New York ;a| Chichester, West Sussex :b| Columbia University Press,c| [2026];

300 a| xiii, 240 pages :b| illustrations (black and white) ;c| 23 cm.;

336 a| textb| txt2| rdacontent;

337 a| unmediatedb| n2| rdamedia;

338 a| volumeb| nc2| rdacarrier;

490 1 a| Race, inequality, and health;

504 a| Includes bibliographical references and index.;

520 a| "From social science and biomedical research to government and media reporting, statistics on racial and ethnic disparities are everywhere. The numbers we typically encounter, however, are not straightforward comparisons. Researchers analyze data using adjustments such as regression models that are intended to address bias and confounding factors. Yet many common statistical practices produce misleading results, and some have flawed assumptions that inadvertently misrepresent the inequalities between groups. Jay S. Kaufman offers a clear and accessible guide to understanding the use and abuse of statistics on racial and ethnic disparities. Examining dozens of real-world examples spanning medicine, economics, education, and criminal justice, he shows how typical statistical practices - no matter how well-intentioned - have obscured the realities of injustice, with significant consequences for public policy. Kaufman considers how to select and apply statistical adjustments responsibly and systematically, and he proposes ways to improve the explanation and analysis of racial and ethnic inequalities. Written for readers without a background in statistics, this book provides an essential introduction to quantitative reasoning in terms of social justice" --c| Publisher's description.;

650 0 a| Race discriminationx| Researchx| Statistical methods.=| ^A4513;

650 0 a| Racismx| Researchx| Statistical methods.=| ^A46371;

650 0 a| Social justicex| Researchx| Statistical methods.=| ^A6160;

650 0 a| Statisticsx| Social aspects.=| ^A1380;

650 7 a| Race discrimination2| fast;

650 7 a| Racismx| Research2| fast;

650 7 a| Social justice2| fast;

650 7 a| Statistics2| fast;

776 08 i| ebook version :z| 9780231559942;

830 0 a| Race, inequality, and health.?| UNAUTHORIZED;

949 a| Order on Demandw| ASISh| JOYNER219;

960 o| 1s| 32.00u| JSOCz| USD;

961 f| DMDm| 138099;

596 a| 1;

998 a| 6722246;

999 a| ORDER ON DEMANDw| ASISc| 1i| 6722246-1001l| JYBPDDAPm| JOYNERr| Ys| Yt| JYBPDDAPUu| 4/21/2026;

The race variable : how statistical practices reinforce inequality / Jay S. Kaufman.

Author/creator	Kaufman, Jay S., 1963- author.
Format	Book
Publication	New York ; Chichester, West Sussex : Columbia University Press, [2026]
Copyright Date	©2026
Description	xiii, 240 pages : illustrations (black and white) ; 23 cm.
Subjects	Race discrimination--Research. --Statistical methods. Racism--Research. --Statistical methods. Social justice--Research. --Statistical methods. Statistics--Social aspects.

Series	Race, inequality, and health Race, inequality, and health. UNAUTHORIZED
Contents	What is this thing called race? -- Causality and the fundamental challenge of observed correlation -- Making other worlds -- Crude versus adjusted racial and ethnic comparisons -- Conditional disparities are the devil's playground -- The mismeasure of man -- Proxies and predictions -- Filters and screens -- Scales, values, and preferences -- What explains a disparity? -- Nature versus nurture.
Abstract	"From social science and biomedical research to government and media reporting, statistics on racial and ethnic disparities are everywhere. The numbers we typically encounter, however, are not straightforward comparisons. Researchers analyze data using adjustments such as regression models that are intended to address bias and confounding factors. Yet many common statistical practices produce misleading results, and some have flawed assumptions that inadvertently misrepresent the inequalities between groups. Jay S. Kaufman offers a clear and accessible guide to understanding the use and abuse of statistics on racial and ethnic disparities. Examining dozens of real-world examples spanning medicine, economics, education, and criminal justice, he shows how typical statistical practices - no matter how well-intentioned - have obscured the realities of injustice, with significant consequences for public policy. Kaufman considers how to select and apply statistical adjustments responsibly and systematically, and he proposes ways to improve the explanation and analysis of racial and ethnic inequalities. Written for readers without a background in statistics, this book provides an essential introduction to quantitative reasoning in terms of social justice" -- Publisher's description.
Bibliography note	Includes bibliographical references and index.
Issued in other form	ebook version : 9780231559942
ISBN	9780231213639
ISBN	023121362X (hardcover)
ISBN	9780231213622 (hardcover)
ISBN	0231213638 (paperback)
ISBN	ePub ebook

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