TEACHERS’ EXPERIENCES IN ENGAGEMENT WITH PARTNERS IN ENVIRONMENTAL AND SUSTAINABILITY EDUCATION
Bibliographic record
Abstract
This thesis is an assessment of how Canadian teachers and principals engage with organizational, business, corporate, and individual partners to enhance environmental and sustainability education (ESE) practice in K-12 schools. The research of this thesis was drawn from data collected for a national comparative case study by the Sustainability and Education Policy Network (SEPN). This thesis study analyzed interview transcripts, numerical ratings, and survey questions. Conclusions were drawn through the comparison of teacher comments and ratings to current education policy regarding partnerships in their regions. Results suggested the influence of policy or lack of policy on practice in a variety of contexts. Data showed most teachers and principals mentioned a specific partner by name when discussing their ESE teaching, implying that partnering with out of school entities is common practice despite little to no policy guiding partnership activities. Teachers tended to mention more partners by name in rural divisions when compared to teachers in urban settings. Some teachers were ‘super-connectors,’ noting far more partnerships than others. Results suggest that teachers tend to be the primary initiators of ESE school-based partnerships. A wide variety of partners were mentioned, but non-governmental organizations (NGOs) were by far the most prevalent. There was also a great diversity in the activities and outcomes resulting from partnerships, though a common theme was that partnerships allowed for lessons that were experiential and regionally specific. This thesis concludes with suggestions for teachers who desire to work with organizations, and recommendations for policy makers regarding how policy could better facilitate and optimize partnerships in furthering environmental and sustainability education.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".