Understanding the Early Career Teachers’ Needs: Findings from the Pan-Canadian Survey
Bibliographic record
Abstract
Socialization of early career teachers (ECTs) across Canada is situated within the dynamic contextual landscape which both influences their development and practice and also dictates professional expectations. Our pan-Canadian research study examined the differential impact of induction and mentorship programs on ECTs’ retention across the provinces and territories of Canada. This article outlines the results from a pan-Canadian Teacher Induction Survey (N=1343) that examined ECTs’ experiences with induction support, mentorship, working environment, and career development. Our findings showed that despite geographic, contextual and policy differences, there were similarities in the needs of ECTs regarding the induction, mentoring, and administrative supports for career development. This study provides insight and feedback about what is working well and what might be improved upon in terms of policies, initiatives and processes for mentoring, induction, and retention practices for the early career teachers in Canada.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".