Using First Nations’ narratives and oral histories to inform land-use plans: creating a prototype to aid future planning
Bibliographic record
Abstract
Many Canadian Indigenous communities are planning for their Traditional Territories and resource management areas by reclaiming the land-use planning process. This is being achieved through the application of cultural knowledge and governance traditions to the development of long-term visions for their communities and Traditional Territories. A key component of this reclamation process is use-and-occupancy mapping. While this process is successful at highlighting spatial data it does not highlight non-spatial data such as narratives and oral histories. This practicum uses qualitative analysis to analyze existing First Nations’ land-use plans in order develop a prototype coding framework in which non-spatial data could be drawn out of use-and-occupancy interview data to further inform land-use plans. Findings suggest that analysis completed with the prototype can be used as a direction for further exploring non-spatial data that could be used to further inform First Nations land-use plans and management practices.
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".