The job performance of Canadian educators: the relative importance of the task, teaching conditions and relations between students and teaching team
Bibliographic record
Abstract
The school population evolution and the many new tasks under teacher responsibilities encourage researchers to question about the teachers’ status and conditions. In this article, based on empirical data gathered from Canadian educators (2006), we are concerned about the performance of educators in this complex and evolving work called teaching, but also we re looking for factors that explain its variation. Overall, the results show that the performance of educators’ work is significantly associated with the workload and working conditions but also the social relationships that surround the daily exercise of the profession. Careful examination of the results leads us to conclude that the influence of social relationships is more important than working conditions. More particularly, relations with students exert an influence much more significant than other factors studied: the more relationships are rewarding, at least as perceived by the teachers, the more teachers have the tendency to attribute positive performance to their profession. And, on the other hand, difficult relations with students have an adverse effect on the professional experience of the educators. The same is true, albeit to a lesser extent, with regard to the quality of relationships with other members of the teaching team.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".