The politics of partnership: Exploring perspectives on indigenous education and state governance in central Canada
Bibliographic record
Abstract
This dissertation explores the contradictions and tensions inherent in state discourses of partnership and collaboration in the realm of urban indigenous education in Central Canada. These partnerships, explicitly aimed at a realignment of the state with indigenous peoples through the creation of school-community alliances and imbued with the symbolic language and normative claims of 'working together', are located within the context of federal and provincial discourses of schooling that construct the role and purpose of education as both transformative and emancipatory and that continually emphasize the educational failure of indigenous students within Canadian public schools. This study begins from the premise that white such naturalized discourses of social progress and inclusion highlight the need for continued attention to the 'indigenous problem' in education, they elide the more complicated theoretical and political questions of power, knowledge construction, epistemology, and indigenous struggles for self-determination that always form an essential part of debates and dialogues in the educational realm as well as the multifarious terrain that has shaped indigenous education since colonial times. ^ Drawing on 16 months of ethnographic fieldwork in the prairie city of Saskatoon, Saskatchewan, the study coalesces around an investigation of one such partnership, the Indigenous Peoples Partnership. The study explains how narratives of collaboration and reform become negotiated in the collective partnership space, highlighting how a vision about the place and purpose of education in the lives of urban indigenous students becomes constructed against a backdrop of national moves toward third way governing. Consequently, I argue that the work of the partnership is partly related to the cultivation of a form of authoritative knowledge, indigenous student subjectivity, and epistemological framework through which efforts around indigenous education in the city become mediated and the social relations governing educational change become mapped. The findings of this study have implications for researchers and practitioners in indigenous education, anthropology of the state, indigenous state-relations in Canada, and minority rights. ^
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.061 | 0.029 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".