Labor Upsurge in the North American Automobile Transition: Towards a New Industrial and Labor Relations Stage?
Bibliographic record
Abstract
Abstract Many scholars have observed that the North American labor movement is experiencing a resurgence. Whilst spanning different economic sectors, the resurgence is a striking phenomenon in the auto sector across all three North American countries. After decades of union decline, concessionary bargaining, and labor laws broken by employers and pro-business governments, a new labor movement momentum has become a common feature of the post-pandemic “new normal.” This resurgence is manifested in increased labor rights and collective bargaining gains coupled with a socially sanctioned union voice to fight back for better wages and working conditions and the right to engage freely in union organizing and collective bargaining. Conceptually, the structural, associational, societal, and institutional power exercised by labor are all gaining in strength. This became most apparent across North American countries during the 2023 automobile labor strikes. The objective of this paper is to analyze the recent labor upsurge in the North American automobile industry. Our thesis is that the labor upsurge is part of a critical juncture unfolding amid a deep transition within the auto industry towards a paradigm of new electric mobilities and a renegotiation of the employment relationship. This opens a window of opportunity for labor to tip the balance of power in its favor. The paper identifies the productive and permissive conditions that both foster and restrain labor’s possibilities, within the context of the industrial and labor regime legacies of each country.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".