Arts teachers' motives, values and perceptions of their work and objectives at Ontario secondary public schools
Bibliographic record
Abstract
The objective of this dissertation is to gain an understanding of the relationship between the arts teachers' perceptions of the objectives served by the public arts secondary schools in Ontario and their own work, values, and motives. Eight arts teachers from four Ontario public secondary schools offering arts programs that are considered to be significant contributors to community culture participated in semi-structured, open-ended elite interviews. Guided open-ended questions addressed the themes of school objectives, arts teachers' own objectives, curriculum expectations, and the effects of their artistic experience on their work in the public secondary arts programs. The analysis of the responses delineated the arts teachers' perceptions of their motivation bases, and indicated their values and priorities that guide the educational decision-making processes. The study revealed that there was a strong influence of teachers' extracurricular professional knowledge of the arts on art teachers' values, which was guiding their pedagogical decision-making. The participants' context-sensitive dual motivation bases of consequence and preference were reflective of their dual role as artists and teachers. Their perceptions and motivation bases found an application as a contextual ground for the resulting decision-making prioritization among available pedagogical approaches.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".