Working in the Air: Time Management and Work Intensification Challenges for Workers in Commercial Aviation
Bibliographic record
Abstract
In the air transport sector, the work of flight attendants is characterised by the diversity of their temporalities and working hours. The constraints of working time have impacts on the organization of other activities and social times of the staff. This text shows the diversity of working hours and the way they are articulated to other temporalities, in a working context where the cabin crew is constantly changing, working on different temporary teams. The paper analyses the regulations, the definition of working time and the specific method of calculating this chronological time dedicated to the work activity. It shows the intensification of work experienced by the flight attendants, the fragmentation and heterogeneity of working times. The constraints of atypical working hours are analysed through timetables and the tensions experienced between professional, family and personal times. Professional activities are characterised by a diversity of working and non-working times that are strongly interconnected. Some national particularities highlighted can offer interesting solutions to several difficulties experienced elsewhere and illustrate ways of adjusting or getting around the working time issues specific to the work of the flight attendants. This paper is based on theoretical and empirical research carried out with air hostesses, stewards and pursers employed in several regular, low-cost and charter airlines in Canada and in several European countries.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".