Fostering Meaningful School Engagement Among Indigenous Students
Bibliographic record
Abstract
Students can play a significant role in school decision-making; education practice and reform; reimagining teaching and learning; democratizing education; and schooling improvement. Sociology of education and youth literature demonstrates a strong connection between student engagement in schooling and student academic achievement as well as a sense of belonging to a school community. These insights have particular relevance for Indigenous students in kindergarten to grade 12 schools. Canadian education policy and practice, reinforced by the Truth and Reconciliation Commission’s Calls to Action, have prioritized the need to support Indigenous students while including Indigenous perspectives and experiences in curriculum. We report on a community-based participatory research project to engage and empower Indigenous students connected to one Alberta elementary and junior high school as leaders and education partners. The project focuses on amplifying the student voices through photovoice and is guided by the question: How can schools foster meaningful student engagement and partnership? It draws from work on a photovoice project with two cohorts of students. Students revealed through their photovoice work several components important to their education and schooling, including opportunities for learning about Indigenous cultures, traditions, languages, and spirituality; relationships and connections; environmental protection and conservation; and being heard and respected.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".