“We Will Not Submit:” A Worker’s Inquiry Into The Labor Process Shaping Higher Education’s Labor Upsurge
Bibliographic record
Abstract
This dissertation will examine how the labor process shapes the progression and outcome of strike action.Contemporary scholarly literature on strikes utilizes theoretical frameworks and concepts largely drawn from the study of collective behavior and social movements to understand why and how workers take action (Rhomberg & Lopez, 2021). These scholars provide important insights into how strikers mobilize internal and external resources to wrest concessions from their employers (Dixon & Martin, 2012; Lopez, 2004; Mirola, 2003; Schmalz, Ludwig, & Webster, 2018; Kallas, 2024), how strikers “frame” or make meaning out of their conditions in order to mobilize one another (Schmitt 1993; Conell & Conn, 1995; Martin, 2003; Coley, 2015; Danaher & Dixon, 2017; Levine, Cobb, & Roussin 2017), how workers’ perception of political opportunities and threats may spur collective action (Barrie & Ketchley, 2018), and how differences in strategic capacity shape the efficacy of workplace organizing (Ganz, 2009). However, unions are not social movement organizations and workers differ from other movement activists in important ways (McAlevey 2015; Rhomberg & Lopez, 2021). This dissertation will argue that, while social movement literature has been a useful resource for those studying labor movements, it fails to capture a key determinant underpinning the shape of strike action: the labor process. To advance my argument, I will analyze a series of strike actions that took place amongst academic workers at the University of California, Santa Cruz between 2019 and 2024. Drawing on the varied tradition of workers’ inquiry, I utilize movement ephemera, internal and external communications, collective writing projects, original photographs, and workers’ own account of their strike action(s) to demonstrate how the academic labor process (teaching and research, specifically) influenced strategy, tactics, and the feelings of collectivity necessary to sustain militant action.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".