Time Warped: The Flexibilization and Maximization of Flight Attendant Working Time*
Bibliographic record
Abstract
Le temps de travail a été le sujet de débats et de luttes tout au long de l'histoire du capitalisme industriel, et le contexte actuel de transformation économique et sociale rapide a sur lui de profondes répercussions. Au moyen d'une étude de cas des nouvelles réalités de temps de travail des agentes et agents de bord d'Air Canada, cet article aide à améliorer notre compréhension des répercussions de ces mutations sur les travailleuses et travailleurs dans notre économie de services en pleine croissance. Je veux montrer que le régime de temps de travail de l'aviation commerciale de l'époque de la mondialisation‐déréglementation a renforcé la réification de la force de travail des agentes et agents de bord. Working time has been the subject of debates and struggles throughout the history of industrial capitalism, and the current context of rapid economic and social transformation is having profound repercussions on it. Through a case study of the new working‐time realities of flight attendants at Air Canada, this article helps fill the gap in our understanding of the impact of changing temporalities on workers in the ever‐expanding service economy. I demonstrate that the globalization/ deregulation‐era airline‐industry working‐time regime has deepened the commodity status of flight attendant labour power.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".