The Work of Elementary Principals in Supporting New Teachers in Ontario, Publicly-Funded, English Speaking Schools
Bibliographic record
Abstract
Teachers benefit from instructional, emotional, institutional and physical supports in their early years of practice (Lipton & Wellman, 2003). Yet, with a teacher surplus in Ontario, many early career teachers (ECTs) spend years in transient, short-term work prior to qualifying for the New Teacher Induction Program (NTIP). As school leaders, Ontario elementary principals develop and facilitate supports for the ECTs in their school. However, principals have identified their workloads to be demanding and intensifying (Pollock, 2014b). ECT support development is one of many responsibilities that principals undertake in their work.\nThis qualitative study employed semi-structured interviews with twelve elementary principals from five school districts in Southern Ontario, Canada to explore these issues and investigate the work of principals in supporting the ECTs in schools. Specifically, this study examined how elementary principals understand ECT supports. It recorded the strategies principals employed to develop and facilitate the supports for ECTs. The influence of ECT support policy on principal work was considered along with the challenges that principals identify in their development and facilitation of supports.\nThe findings indicate that principals found their work in developing and facilitating ECT supports to be meaningful. Supports were considered an investment in ECTs and principals recognized priority in their support development for the ECTs that invest in their school and teaching practice. Principals indicated challenge in scheduling the development and facilitation of new teacher supports within their intensifying workload. Lastly, a potential policy gap between ECTs being hired and qualifying for NTIP meant principals were not always able to develop and facilitate supports for some of the ECTs that are engaged in short-term teaching assignments, leaving informal supports and self-directed learning as interim solutions until those ECTs gained consistent teaching work.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".