Bibliographic record
Abstract
For anyone who teaches the history of the civil rights movement, this book is a must-have. Led by the historian Hasan Kwame Jeffries, twenty-four scholars contributed essays to provide example after example of pedagogical methods, classroom activities, source materials, and creative ideas to make the civil rights movement come alive for our students. The throughline of this important work is an attempt to understand why so many K–16 students still only learn about the civil rights movement's “Master Narrative,” and what educators can do to broaden, enrich, and more accurately tell the story. Julian Bond coined the facetious Master Narrative term to dispel this shallow telling of history, one that focused on men, famous leaders, politicians, events the national media chose to cover, the American South, and a warped understanding of nonviolence. Over the last quarter century, historians have dismantled these tropes, but the challenge remains over how best to...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".