The green Don Quixotes : values development of Education for Sustainable Development teachers
Bibliographic record
Abstract
We, as a society, have been presented with a massive problem to solve. As the northern hemisphere (and increasingly parts of the southern hemisphere) continue efforts for economic growth, security, and personal comfort; topics of ecological damage, climate change, hunger, disease, poverty, exploitation, and war become more and more commonplace in our collective psyche. In order to find solutions, we must stop using old ways of thinking in favor of a ‘new story’, one that places humans within nature instead of in control over it. While top level efforts are important, even more critical to this topic are the people charged with teaching these new ideas, beliefs, and behaviors. The question that arises from this is, what are the beliefs and values of the teachers who are viewed as passionate or leaders in the field of Education for Sustainable Development (ESD)? What have they learned or experienced that has led them to teach from an ecologically literate perspective and/or towards a greater understanding and acceptance of social responsibility? This study collects the stories and experiences of six high school science teachers and ESD practitioners currently working in Winnipeg, Manitoba, Canada. Stories were analyzed to discover: individual values and belief sets of teachers as well as their progression from childhood to novice teacher to ESD practitioner; and experiences that promoted currently held beliefs and values. As a result, the data shows ESD practitioners to be dedicated and committed individuals, whose values and attitudes stem directly from childhood experiences in nature coupled with parental/adult encouragement. From their stories and experiences, it is clear that successful implementation of values based ESD programs rests sole on the shoulders of the people asked to teach it.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".