T<scp>obias</scp> H<scp>igbie</scp>. <i>Labor’s Mind: A History of Working-Class Intellectual Life</i>.
Bibliographic record
Abstract
Tobias Higbie’s Labor’s Mind: A History of Working-Class Intellectual Life is a slim volume with an expansive reach. The book explores workers’ intellectual pursuits and projects in the 1920s and 1930s, the emergence of extensive working-class intellectual movements on street corners and institutions alike, and the uses and limits of the image of the worker-intellectual through the interwar period into the postwar era. More broadly, though, it suggests that education, formal or informal, can spark radical social change. Higbie begins by exploring the role of self-education in the labor movement of the 1920s. The majority of Americans—regardless of class, national origin, or race—were literate, and workers devoured books of all sorts, from economics textbooks to plays to pulp fiction. We know the most about workers who parlayed their reading into leadership roles in the labor movement, but rank-and-file workers were avid readers as well. Though their “book learning” rarely translated...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.093 | 0.043 |
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 source (direct Gemma or distilled Codex), 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".