From Faceless to In-Your-Face Bosses: Work in Neo-Feudal America. Coerced: Work under Threat of Punishment. By Erin Hatton (2020) Oakland: University of California Press, 281 pages. ISBN: 978-0-520-30539-7. Bite Back: People Taking on Corporate Food and Winning. Edited by Saru Jayaraman and Kathryn De Master (2020) Oakland: University of California Press, 312 pages. ISBN: 978-0-520-28936-9. Hustle and Gig: Struggling and Surviving in the Sharing Economy. By Alexandra J. Ravenelle (2019) Oakland: University of California Press, 273 pages. ISBN: 978-0-520-30056-9. Uberland: How Algorithms Are Rewriting the Rules of Work. By Alex Rosenblat (2018) Oakland: University of California Press, 271 pages. ISBN: 978-0-520-29857-6. Bandage, Sort and Hustle: Ambulance Crews on the Front Line of Human Suffering. By Josh Seim (2020) Oakland: University of California Press, 249 pages. ISBN: 978-0-520-30023-1.
Bibliographic record
Abstract
An article from Relations industrielles / Industrial Relations, on Érudit.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".