Environmental monitoring for the 21st century: Exploring Indigenous evaluations of the Canadian government’s Indigenous Guardians pilot program
Bibliographic record
Abstract
In response to the exclusion of Indigenous people from natural resources management, the Canadian federal government announced that they would provide $25 million over four years to support the development of Indigenous Guardians programs across Canada. The program was promised to “provide Indigenous Peoples with greater opportunity to exercise responsibility in stewardship of their traditional lands, waters and ice” (Government of Canada 2020). I used a case study approach to explore the role of this funding to support Indigenous communities in their Guardians initiatives. I facilitated semi-structured interviews with staff from five Indigenous Guardians programs from BC and Manitoba, Canada. Participants suggested that the federal pilot program was a step in the right direction to support environmental stewardship initiatives led by Indigenous governments or communities. In particular, this program was successful in increasing monitoring of the land, collaboration with like-minded groups, and facilitating the education of youth by community Elders.
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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 | 0.027 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| 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".