Counting the minutes: Administrative control of work schedules and time management of secondary school teachers in Québec
Bibliographic record
Abstract
UNLABELLED: Québec teachers have been identified as having a high level of stress and having difficulties with work-family balancing (WFB). An analysis of their work activity was done to identify task elements that could be changed. PARTICIPANTS: Work of 15 teachers was observed and 20 other teachers were interviewed. METHODS: Ergonomic analysis, a mixed method that combines qualitative analysis with some quantitative data: 87 hours' observation; 15 interviews. Environmental parameters were recorded in 8 classrooms and in two faculty workrooms. Working postures were recorded. RESULTS: Teachers were subject to numerous demands in an often inadequate environment. A new management practice required teachers to spend 300 min/week outside class but in school, where their work could be monitored. The timed and scheduled tasks could not be done in the rooms provided due to overcrowding, inadequate physical environment, and lack of access to computers and telephones. Time at home decreased but work done at home did not. CONCLUSIONS: The physical environment of teaching impacts teaching activity. Work organization that treats a complex, results-oriented task as if it could be well represented by the number of supervised minutes spent on it can be problematic. WFB should be considered when work is re-organized.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".