Bibliographic record
Abstract
Noting that accounts of deindustrialization in the United States, reflecting organizing efforts to reverse the trend, have tended to emphasize individual cities, Steven High takes a broader and potentially richer approach. By including the Canadian portion of the Great Lakes region most severely damaged by disinvestment, he seeks to demonstrate the central factors affecting the ability of workers to determine their own fates. Drawing on a number of cultural as well as economic and political factors, he argues that Canadians fared better than their counterparts in the United States. The weight of his own evidence suggests, however, that in neither case was labor a match for the power and influence of multinational corporations. In the United States, High reports, manufacturing employment declined by 22.3 million jobs during the recession years 1969 to 1976. Calling organizing efforts to block plant closures “a miserable failure” (p. 133), he blames both unions, for relying on campaigns for trade protectionism at the expense of legislation to compensate and retrain workers, and new left activists, whose antinationalist attitudes dating from the Vietnam War confined their actions largely to local arenas. To illustrate the limits of effective coalition building, he cites labor's refusal to support efforts headed by the historian and former antiwar activist Staughton Lynd to support community ownership of abandoned plants in Youngstown, Ohio.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.194 | 0.049 |
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".