The state of indigenous research in Canada: a review of canadian university graduate and post-graduate theses 2010-2015
Bibliographic record
Abstract
There is currently a lot of academic work being conducted in the area of Indigenous studies by Canadian scholars. In particular, attention has been given to the paradigm shift in Indigenous studies where the participatory focus is on benefiting Indigenous communities, versus mere academic exercise. Amongst all of the attention given to the paradigm shift in Indigenous methodology, it can be difficult to get an understanding of what themes of research have been under-explored and how a researcher could best support the research field. This thesis sets out to identify priority areas of Indigenous research, research themes that are under-researched, and the state of Indigenous research conducted by the academic community in Canadian Universities. This qualitative study examines a representative sample of graduate and post-graduate theses on Indigenous studies between the periods of 2010 to 2015 and qualifies them according to the 25 themes identified as priority, by the Social Sciences and Humanities Research Council (SSHRC). The results from this research show that the categories ranked as top priority are Indigenous justice, urban issues, Indigenous identities, Indigenous languages and traditions, economies and labour studies, governance and sovereignty, Indigenous humanities and culture and lands and environment. This study shows when comparing sampled theses to priority themes, with the exception of research pertaining to land, and Indigenous humanities, ongoing research in these categories is still required. It is determined that the acknowledgement of the paradigm shift in Indigenous research has been successful in the production of Indigenous study themes that are in line with the determined priorities and methodologies.
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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 | 0.019 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.023 | 0.058 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".