Including Indigenous Knowledges and Pedagogies in Science-based Environmental Education Programs
Bibliographic record
Abstract
In exploring ways to respectfully include Indigenous Knowledges and pedagogies within environmental education programs, the challenge is to ensure strategies used will meaningfully support learning while reflecting local cultural traditions, languages, beliefs, and perspectives. In this paper, key components for science-based environmental education programs that include Indigenous Knowledges and pedagogies are considered, along with a possible means to evaluate the effectiveness of attempts to make these programs more culturally responsive. Ininiwi-kiskānītamowin, a model for science and math programming in Indigenous settings, is applied to a culturally relevant environmental education program called Bridging the Gap (BTG). Evaluating BTG within the context of the Ininiwi-kiskānītamowin model generates an enlightening illustration of the nature of the model as a process of lifelong learning, and suggests the need to consider alternative pedagogies and educational frameworks when developing and evaluating culturally relevant environmental education programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".