Becoming a Sustainability Chef: An Empirical Model of Sustainability Perspectives in Educational Leaders
Bibliographic record
Abstract
This dissertation reports a study exploring adult engagement with sustainability learning practices in EcoSchools-certified secondary schools in Canada, Lithuania and Sweden as a means towards shaping a liveable future. The study is situated in the area of education for sustainable development. The study design was initially based on an interest in revealing specific practices of sustainability education as a means of improving the relationship between environmental impact and wealth. While echoing findings in the existing literature, this research contributes to the development of the field through insight into the perspectives that adults bring to sustainability education. Primary data collected in the spring of 2006 were recorded (mostly single) semistructured interviews with 30 individuals (national coordinators, caretakers, teachers and administrators), including 10 Canadians from four schools, 14 Lithuanians from four schools, and six Swedes from two schools. Four phases of qualitative analysis were used on the data: initial transcript coding and trends; précis document trends; a six-stage model of interview responses allowing vertical (between question) and horizontal (between stage) comparisons; word maps of subthemes as a scaffold to detail participants’ four primary views (long, wide, deep, dynamic) regarding sustainability. Ultimately, the results of this study point less than expected to revealing specific transferable practices regarding success and challenge in EcoSchools. Rather, these findings provide some insight into a means of shaping a sustainable future through an individual’s sustainability perspective: a living responsiveness based on a sense of connection, supported by improved sustainability cognition, and realized through sustainability practice and considered engagement.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".