Making Kin with Multispecies’ Flourishing in the Anthropocene: A Multiperspectival Narrative Into Environmental and Sustainability Education
Bibliographic record
Abstract
The development of Environmental and Sustainability Education (ESE) in pre-service teacher education in Canada has shown slow but steady progress over the past 40 years. A detailed history of how individuals and groups have influenced its praxis does not yet exist (Elliott & Inwood, 2019, p. 37). This paper attends to the experiences of six teacher educators/graduate students who have been composing their lives in different landscapes in relation to ESE. We employ collaborative autoethnography as our research methodology. Together, we are involved in the process of telling, retelling, and reliving our stories of who we are in relation to ESE. We also pay deep attention to the resonances echoed across our experiences and curate our forward-looking thoughts for/with the future of ESE. We hope to expand current ESE with a more holistic and sustainable approach, which includes integrating place-based wisdom with environmental education; collaborating with material presences not as resources but as partners for multispecies’ flourishing; and sustaining the intergenerational reverberations of familial and cultural practices and quantitative literacy. Le développement de l'éducation à l'environnement et à la durabilité (EED) dans la formation initiale des enseignants au Canada a connu des progrès lents mais constants au cours des 40 dernières années. Il n’existe pas encore d’histoire détaillée de la manière dont les individus et les groupes ont influencé sa pratique (Elliott & Inwood, 2019, p. 37). Cet article s’intéressé aux expériences de six formateurs/étudiants diplômés qui ont composé leurs vies dans différents paysages en relation avec l’EED. Nous employons l'autoethnographie collaborative comme méthodologie de recherche. Ensemble, nous participons au processus de raconter, de redire et de revivre nos histoires en relation avec l'EED. Nous accordons également une grande attention aux résonances de nos expériences et rassemblons nos pensées prospectives pour/avec l’avenir de l’EED. Nous espérons développer l'EED actuelle avec une approche plus holistique et durable. Celle-ci inclut l'intégration de la sagesse locale à l'éducation environnementale, la collaboration avec les présences matérielles non pas comme des ressources mais comme des partenaires pour l'épanouissement de plusieurs espèces, ainsi que le maintien des réverbérations intergénérationnelles des pratiques familiales et culturelles et de la littératie quantitative.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.040 | 0.062 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".