Approaches to Bio-Cultural Diversity in British Columbia
Bibliographic record
Abstract
This paper highlights an action research project into some decolonizing practices for environmental learning in the Canadian context of the British Columbia (BC) curriculum through case study and focus groups with Indigenous educators. A key finding taken from these discussions is that educators must strive to learn with Indigenous people not about them as the process of decolonization is about acknowledging multiple knowledge and value systems. We hosted two consultations with groups of Indigenous knowledge holders in the process of our work. The first consisted of a purposeful sample of Indigenous educators and academics drawn from Coast Salish communities in and around urban regions in coastal British Columbia (N = 20), the second draws on a purposeful sample of rural Indigenous educators and academics drawn from the Okanagan valley and British Columbia Interior (N = 10). The vignettes we share focus on how educational policy can be infused with Indigenous knowledges and pedagogical perspectives and, respectively, how policy changes might inform instruction on climate change education and a variety of other environmental topics. The revised framework we produce will guide teachers in their educational planning and support the implementation of environmental learning in diverse subjects using the dual lenses of bio-cultural diversity and inquiry—teaching about the environment and Indigenous knowledges together as an organizing theme for all teaching and learning. Our work highlights key aspects of our research involving practicing teachers, academics, provincial Ministries of Education and Environment as well as the Canadian Commission for UNESCO. The research articulates several important bridge-building activities: one linking research and policy, one bridging theory with practice, and most importantly, one bridging the inherent synergies among Indigenous and environmental knowledges.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.047 | 0.026 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".