Teachers Working in the Field of Environmental Education: Musings of a Practitioner
Bibliographic record
Abstract
Over the last century, much was researched in the field of Education, be its educational policies or more effective learning strategies. It is only recently that studies have begun to focus on the teachers. This article describes an investigation about how the knowledge of teachers working in the field of Environmental Education is formed, transformed, and accessed. For this purpose, an ethnographical study of their narratives and practices was carried out. With the new century unfolding, it seems relevant to re-evaluate our learning purposes, as Education is considered to be an essential tool for the preservation of life on Earth. As teachers are privileged professionals in this process, elaboration of a new repertoire of professional teaching practices seems pressing. Resume Depuis le siecle dernier, on a fait beaucoup de recherche dans le domaine de l’education, que ce soit sur ses politiques ou sur ses strategies d’apprentissage plus efficaces. Ce n’est que recemment que les etudes ont commence a cibler les enseignants. Cet article decrit une recherche sur comment le savoir des enseignants qui travaillent en education environnementale est forme, transforme et transmis. Dans ce but, on a conduit une etude ethnographique de leurs recits et de leurs pratiques. Avec le nouveau siecle qui debute, il semble pertinent de reevaluer nos intentions en apprentissage puisqu’on considere l’education comme un outil essentiel pour la preservation de la vie sur terre. Et comme les enseignants sont des professionnels privilegies de ce processus, l’elaboration d’un nouveau repertoire de pratiques professionnelles en enseignement semble presser.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".