Symposium on Barry Eidlin’s <i>Labor and the Class Idea in the United States and Canada</i>
Bibliographic record
Abstract
Abstract Barry Eidlin’s book, Labor and the Class Idea in the United States and Canada (Cambridge University Press, 2018) explains why unions are weaker in the United States than they are in Canada, but have not always been that way. Indeed, unionization rates were virtually identical for much of the twentieth century, then diverged in the 1960s. Against dominant accounts focused on long-standing differences in political cultures and institutions, Eidlin argues that the divergence resulted from different ruling party responses to working class upsurge in both countries during the Great Depression and World War II. In Canada, an initially more hostile state response ended up embedding “the class idea”—the idea of class as a salient, legitimate political category—more deeply in policies, policies, and practices than in the United States, where class interests were reduced to “special interests.” In this symposium, three noted labor scholars engage critically with the book. Cedric de Leon interrogates Eidlin’s account of the role of racial divisions in explaining divergence, noting “more persistence and convergence than there is rupture and divergence” between these two countries on this issue. Nelson Lichtenstein’s critique focuses on the exceptionally vociferous character of US employer hostility, which he argues that Eidlin downplays. And Judith Stepan-Norris notes the surprising lack of actual class actors in a book about class organization, while raising interpretive questions about the relation between labor and the Communist Party in both countries. Eidlin concludes the symposium with a response to the critics.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.044 | 0.021 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".