Aboriginal student strength to persist and Indigenous Knowledges in community colleges
Bibliographic record
Abstract
Purpose – The purpose of this paper is to document experiences of Aboriginal students in community colleges from the perspective of Aboriginal communities rather than policymakers and shows how these communities support student persistence in college. Design/methodology/approach – Interviews with 16 Aboriginal college students, staff and community members were undertaken with Aboriginal guidance, and analysis was undertaken informed by the writings of Aboriginal scholars. Findings – The major finding was that First Nations students experience a disconnect between the epistemology of Aboriginal peoples and ways of being in community colleges. Most demonstrate bravery and persistence in their studies as well as resistance to assimilation. Understanding and support is provided by surrounding Aboriginal communities, based on their appreciation of the epistemological roots of the problem. Practical implications – Frequent reference to the absence of Indigenous Knowledges suggests that more must be done to make Aboriginal students feel safe in colleges where they are in the minority. In view of their feeling of “disconnect,” safe Aboriginal centers, or “homes away from home” are one of many ways to support these students. Originality/value – The research challenges assimilationist approaches to Aboriginal college students, and highlights supporting Indigenous peoples, as described in global terms by Indigenous scholars.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".