Elementary School Office Managers' Positive Extra-role Behaviours
Bibliographic record
Abstract
Elementary School Office Managers represent a workforce of over 5000 individuals within the province of Ontario. While their impact on the school is known to the principals, teachers, students, and parents with whom they interact on a regular basis, their contributions have scarcely attracted the attention of educational scholars. Through the lens of Public Service Motivation theory and Extra-Role Behaviour theory, this research sought to identify the personal and work environment influences that impact Elementary Office Managers' Positive Extra-Role Behaviours in Ontario's elementary schools. Through face-to-face interviews with retired elementary office managers, this research found that principal/leader supportiveness, job satisfaction, and individual characteristics were key influences on research participants' positive extra-role behaviour. Possible implications of this research for school districts include: giving consideration to office manger applicants' pre-employment experiences; targeted training for principals on how to nurture office managers' extra-role behavior; the role of the union as detractor to extra-role behaviour, and rethinking the office manager's job description.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 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".