"If you want blood": violence at work in the North American auto industry, 1960-1980
Bibliographic record
Abstract
Violence in the workplace has attracted widespread scholarly and media attention in the United States and Canada since the 1980s. Governments and corporations on both sides of the border have identified this violence as a serious problem affecting the health and safety of workers. However, there is still much that is unknown about workplace violence. Is the problem of workplace violence more serious than it was today? How has it changed over time? What are the factors that have produced violence at work? How have workers, management, and governments defined violence at work? How have they approached the problem? This dissertation historicizes the phenomenon of workplace violence, investigating on-the-job violence in the North American automotive industry between 1960-1980. It embeds violence at work in its economic, political, and cultural contexts and investigates how violence shaped the North American workplace and identities of class, gender, and race on the job. A comparative, transnational approach is central to this study. If we seek to understand the structural factors causing workplace violence, the national context cannot be ignored. This is especially true when considering the US and Canada, two countries which are extraordinarily integrated economically but often contrasted socially and culturally. My research has uncovered a significant history of violence in the automotive workplaces of Detroit and Windsor, and shows that national and local contexts were crucial in determining the level of violence. Violence was a regular element of shop-floor culture and workplace conflict in both countries, but was different in each. In Detroit, violence at work reached epidemic levels and was a major factor in the crisis that gripped the city's auto plants in the 1960s and 1970s. This was not the case in Windsor. Yet in both cities workplace violence became a major concern outside the factory when work-related murders seized national headlines and challenged citizens to understand these tragedies. The thesis demonstrates that, though the patterns and levels of violence were different in each place, violence was no aberration, no freak occurrence, but an ongoing phenomenon that influenced the labour process and workplace culture in both Detroit and Windsor.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".