Bibliographic record
Abstract
This contribution addresses key issues around the application of Indigenous knowledge in contexts where such knowledge is neither generated nor held (academy, industry, governments, etc.). Effective models for the ethical incorporation of Indigenous knowledge into environmental governance in Canada have remained elusive despite decades of attempts. The predominant research paradigm of “incorporating” Indigenous knowledge into environmental governance is one of extraction by the external interests who seek to include specific aspects of such knowledge in their undertakings. This approach continues to fail because Indigenous knowledge exists as an integral component of Indigenous Knowledge Systems (IKS). It is often hollow and potentially damaging to consider any knowledge without understanding the societal systems and peoples that produced it. Indigenous knowledge is not just “knowledge” (a noun) but a way of life, something that must be lived (a verb) in order to be understood. Indigenous knowledge is inseparable from the people who hold and live this knowledge. Although government policy and legislation have evolved in attempts to treat Indigenous knowledge more holistically, the overriding paradigm of extraction remains essentially unchanged. Even the most recent frameworks will meet with limited success as a result. Appropriate and effective inclusion of Indigenous knowledge requires recognition of the systems that support it, which in turn necessitates support for Indigenous self-determination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".