Readers since Thomas Jefferson have believed it possible to judge entire races of people based on a single book, yet no one has attempted to explain the orig...
The State of the People Black Papers | Dr. David J. Johns
The State of the People Black Papers—authored by us for us, free of exaggerated jargon, written plainly in a language for our people
Reading Wars
Read online or download for free Reading Wars explores heated, even murderous, political struggles over who gets to read and what they get to read. Those conflicts, once again in the news, stretch back centuries. In this book, Don Herzog examines the history and politics of anxieties about readers and reading, spanning both the United States and Britain, from the 1500s right up to contemporary battles over banning library books and freedom of speech. In these pages, Herzog deftly interweaves episodes from Reformation England, when first Catholics and then Protestants cracked down on unsupervised Bible-reading, with the deadly campaigns in pre-Civil War America to keep black people – both free and enslaved – illiterate. Drawing on a wealth of primary sources, he reconstructs arguments insisting that ordinary men and women could not be trusted to read what they liked – indeed, that some of them ought not read at all. And he charts struggles to promote literacy. Herzog argues that at stake in these battles is whether some people – those banned from reading – are perceived as not fully human, or lesser persons than others. The radical campaign to let more or less everyone read more or less everything is ultimately, therefore, a campaign for equality. Click here to read praise for Reading Wars "In characteristically engaging and straight-forward language Don Herzog explores the debates past and present, largely in Britain and America, about whether or not to suppress reading. By taking seriously the arguments for suppressing or restricting books and their readers, Herzog suggests that those arguments turn on the claim that for some people reading is dangerous. This assumption, Herzog compellingly argues, ignores the fact that literacy is largely a social activity. In Reading Wars, Herzog develops a powerful liberal argument for literacy and reading. An argument, Herzog shows, that has incompletely triumphed." — Steve Pincus, Thomas Donnelly Professor of History, University of Chicago "Knowledge is power - which is why efforts to acquire knowledge through reading have been outlawed, suppressed through violence, and remain targets today. Don Herzog's Reading Wars tells the astonishing history behind the wars on reading in a readable, clever style, underscoring the stakes of many of the current fights over censorship and book bans." — Leah Litman, cohost of the podcast Strict Scrutiny and New York Times bestselling author of Lawless "A rich yet accessible introduction to the many ways in which society has attempted to restrict reading materials throughout British and United States history. Equal parts illuminating and horrifying, it lays the groundwork for the 21st century’s own shameful dabbles with censorship through its careful consideration of the key concerns and prejudices that structure each generation’s literacy battles." — Alison Hicks, Associate Professor in Library and Information Studies, UCL "Political theory, historical sense, worrisome texts, unheralded documents, and great storytelling join forces in Herzog’s virtuoso investigation of the brutal fighting over who gets to learn to read (and what) in early and late modern America and Britain. The bloodshed may have lessened, but we are still fighting, and Herzog shows the deeper stakes involved in reading’s relation to equality and personhood." — Mary G Dietz, John Evans Professor Emerita of Political Theory, Northwestern University , Reading Wars explores heated, even murderous, political struggles over who gets to read and what they get to read. Don Herzog examines the history and politics of anxieties about readers and reading, spanning the United States and Britain, from the 1500s right up to contemporary battles over banning library books and freedom of speech.
Sam Harris, Charles Murray, and the allure of race science
This is not “forbidden knowledge.” It is America’s most ancient justification for bigotry and racial inequality.
Analytic racecraft: Race-based averages create illusory group differences in perceptions of racism.
How Tommy Robinson Disguises White Supremacism In the Coded Language of Anti-Islam Politics
Robinson repeatedly uses “native” for white, “invader” for non-white and “African” and “Somali” for black across 140 posts examined by Byline Times
The Anti-Defamation League and the Racial State by Emmaia Gelman - Hardcover
Scholarship is a powerful tool for changing how people think, plan, and govern. By giving voice to bright minds and bold ideas, we seek to foster understanding and drive progressive change.
On Tokens and Tokenism - Arts & Letters - Tablet Magazine
From George Washington to Jill Biden, Black literature has long been plagued by ignorant white patrons, who arbitrarily anoint a few writers as symbols ...
Being Black: Selections from "Soledad Brother" by Georg…
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Culture & truth : the remaking of social analysis
xii, 253 pages ; 22 cm; Argues for a new approach to thinking and writing about culture. Exposing old conceptions, the book argues that new ethnographic writing must come to terms with the dynamic nature of social reality - with history, spontaneity, and human emotions; Originally published: Boston: Beacon, 1989; Includes index; Self-Renewing 2017; Includes index
AI generates covertly racist decisions about people based on their dialect
Hundreds of millions of people now interact with language models, with uses ranging from help with writing1,2 to informing hiring decisions3. However, these language models are known to perpetuate systematic racial prejudices, making their judgements biased in problematic ways about groups such as African Americans4–7. Although previous research has focused on overt racism in language models, social scientists have argued that racism with a more subtle character has developed over time, particularly in the United States after the civil rights movement8,9. It is unknown whether this covert racism manifests in language models. Here, we demonstrate that language models embody covert racism in the form of dialect prejudice, exhibiting raciolinguistic stereotypes about speakers of African American English (AAE) that are more negative than any human stereotypes about African Americans ever experimentally recorded. By contrast, the language models’ overt stereotypes about African Americans are more positive. Dialect prejudice has the potential for harmful consequences: language models are more likely to suggest that speakers of AAE be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death. Finally, we show that current practices of alleviating racial bias in language models, such as human preference alignment, exacerbate the discrepancy between covert and overt stereotypes, by superficially obscuring the racism that language models maintain on a deeper level. Our findings have far-reaching implications for the fair and safe use of language technology.
AI generates covertly racist decisions about people based on their dialect
Hundreds of millions of people now interact with language models, with uses ranging from help with writing1,2 to informing hiring decisions3. However, these language models are known to perpetuate systematic racial prejudices, making their judgements biased in problematic ways about groups such as African Americans4–7. Although previous research has focused on overt racism in language models, social scientists have argued that racism with a more subtle character has developed over time, particularly in the United States after the civil rights movement8,9. It is unknown whether this covert racism manifests in language models. Here, we demonstrate that language models embody covert racism in the form of dialect prejudice, exhibiting raciolinguistic stereotypes about speakers of African American English (AAE) that are more negative than any human stereotypes about African Americans ever experimentally recorded. By contrast, the language models’ overt stereotypes about African Americans are more positive. Dialect prejudice has the potential for harmful consequences: language models are more likely to suggest that speakers of AAE be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death. Finally, we show that current practices of alleviating racial bias in language models, such as human preference alignment, exacerbate the discrepancy between covert and overt stereotypes, by superficially obscuring the racism that language models maintain on a deeper level. Our findings have far-reaching implications for the fair and safe use of language technology.
The End of Reading Is Here
Optimists once believed that universal literacy was inevitable. Now it seems that the age of reading might be a short anomaly in human history.
The Racist Beginnings of Standardized Testing | NEA
From grade school to college, students of color have suffered from the effects of biased testing.
Footnotes by Jemar Tisby | Substack
Truth-telling at the intersection of faith, history, and justice Focus on white Christian nationalism + the Black Christian tradition. Click to read Footnotes by Jemar Tisby, by Jemar Tisby, PhD, a Substack publication with tens of thousands of subscribers.
Skin in the game: hidden asymmetries in daily life
From the New York Times bestselling author of The Black…
