173Canadian Journal of Environmental Education, 18, 2013 “This Is More Like Home”: Knowing Nature through Community Mapping
Bibliographic record
Abstract
Place-based environmental education is a pedagogy that infuses environmental education across disciplines in a way that is relevant and meaningful to students. One collaborative approach to place-based environmental education—community mapping—explores and represents local knowledge, visions held by community members, and relationships between spatial, physical, personal, and cultural ele-ments of place. This paper shares a community mapping project done by a British Columbian Grade 4 class and, drawing from Knapp’s (2005) 10 ways of knowing nature, discusses how students came to know nature through observing, situ-ated knowing, identifying, restoring, and transforming. Its findings encourage the inclusion of community mapping in place-based environmental education cur-riculum and instruction, and illuminate the value of the products and process of community mapping. Résumé L’éducation environnementale axée sur le lieu est une méthode pédagogique qui intègre l’éducation environnementale dans toutes les disciplines d’une manière pertinente et digne d’intérêt pour les élèves. Une approche collaboratrice de l’éducation environnementale axée sur le lieu, la cartographie communautaire, examine et représente le savoir local, les visions des membres de la communauté ainsi que les relations entre les éléments du lieu de nature spatiale, physique, personnelle et culturelle. L’article expose un projet de cartographie communautaire réalisé par une classe de quatrième année en Colombie-Britannique et, se fondant sur les « dix façons de découvrir la nature » (Knapp 2005), examine la découverte de la nature par les élèves au moyen de l’observation, l’analyse contextuelle, l’identification, le rétablissement et la transformation. Les conclusions soutiennent l’inclusion de la cartographie communautaire dans les programmes d’éducation environnementale axée sur le lieu et soulignent la valeur des produits et des processus de la cartographie communautaire.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.004 |
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".