The More Things Change, The More They Stay the Same: The Challenge of Identity for Native Students in Canada
Bibliographic record
Abstract
For nearly four decades now, the institutional response to fulfilling the goals of Indigenous cultural revitalization, and addressing the education gap between Aboriginal and non-Aboriginal learners, has relied heavily on a theory of cultural discontinuity. While the enacting of Indigenous culture in educational realms is promoted as a solution to uneven outcomes, and as socially just in general, in-depth examinations of the effects of this emphasis tend to be sparse. This paper elucidates one such analysis, in the process offering a representation of a more or less typical group of urban Native youth; in this case, a group desirous of belonging in an Indigenous sense and highly contemplative about what that has meant for them on an everyday basis. The analysis offered here argues for further consideration of existing solutions in the complicated, complex terrain that is Indigenous education. Rather than proceed along a trajectory whereby Indigenous students are understood as ‘the problem’, resulting in the application of a highly problematic focus on culture, needed at this time is a serious examination of the troublesome realities of cultural fundamentalism and authenticity in Indigenous education, and the manner in which these serve to cover over critical matters concerning race and power.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.049 | 0.014 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".