Work Intensification, Work–Life Conflict and Turnover Intentions in the Teaching Profession: Evidence From School Teachers in Quebec, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Teachers worldwide are expected to adapt to increasingly complex demands. Meanwhile, there is a shortage of qualified teachers in the profession. In this context, our paper explores the role of work intensification (WI) as a predictor of teacher turnover intention, an important antecedent that has never been explored amongst school teachers. The role of work–life conflict (WLC) is also considered, given the salience of this issue according to teacher unions. We distributed an online questionnaire to teachers from various sectors (preschool, primary, secondary, adult training, professional training and special education) through union listings and got 405 valid responses. We ran statistical analyses using PROCESS Macro v.4.2 for SPSS, and our results indicate a direct, significant and positive relationship between WI and intention to leave ( p ≥ 0.001; R 2 = 0.179). Moreover, we found that WLC interacts with WI in its impact on intention to leave ( p ≥ 0.001; R 2 = 0.191). Theoretical contributions are made using the job demands‐resources and conservation of resources theories, and practical implications for government and school leaders are discussed.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it