The Community-First Land-Centred Theoretical Framework: Bringing a ‘Good Mind’ to Indigenous Education Research?
Bibliographic record
Abstract
This article introduces an emergent research theoretical framework, the community-first Land-centred research framework. Carefully examining the literature within Indigenous educational research, we noted the limited approaches for engaging in culturally aligned and relevant research within Indigenous communities. The community-first Land-centred research framework was created by reflecting on how we engaged in research collaborations with Indigenous communities. This process of reflection led us to realize that within our research we had been developing a research framework that was culturally-aligned, relevant, and based on respectful relations that differed in important ways from other community oriented research framework. We articulate how we differentiate this framework from community-based approaches to research and discuss the community-first Land-centred research framework’s foundational principles. We draw upon lessons learned through our various collaborations over the past seven years. Key words: Indigenous; Land-centred research; community engagement
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".