Authenticity in capacity-building for neuroscience: Indigenous scholarship, teaching, and care
Bibliographic record
Abstract
Despite a global push to recognize the value of Indigenous knowledge systems to science and scientific research, neuroscience has largely remained embedded in Western and Eurocentric ways of knowing and doing. Major contributors to this phenomenon include the low representation of Indigenous Peoples in the neurosciences worldwide that stems, at least in part, from a long-standing neglect of Indigeneity in Western academic institutions. Past experiences with exploitation where Indigenous Peoples have historically been treated as subjects to be studied and not collaborative partners to be respected has further compounded the problem. Support systems to recruit and retain Indigenous People as neuroscientists, neurologists, and psychiatrists among others have evolved over time in response, but success is still limited. Inclusive and non-exploitive capacity building is therefore a needed key strategy to entwine Indigenous ways of knowing and doing into neuroscience research and training, and diversify and authentically strengthen research and clinical care strategies.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".