Canadian School Psychology and Indigenous Peoples: Opportunities and Recommendations
Bibliographic record
Abstract
School psychologists play important roles in working alongside Indigenous Peoples within Canada; however, a large gap exists between the discipline’s actions and the recommendations set forth by Indigenous Nations and governmental working groups. In this conceptual article, we seek to highlight the need for further Indigenous representation and engagement in the field of school psychology, as well as present key areas of relevance. We first briefly contextualize the relationship between Indigenous Peoples and school psychology, followed by the results of a brief survey concerning Indigenous representation and engagement across five school psychology doctoral programs in Canada. Next, we discuss nine key areas of consideration for school psychologists based on the Calls to Action of the Truth and Reconciliation Commission of Canada and the Calls for Justice of the National Inquiry into Missing and Murdered Indigenous Women and Girls. Each area of consideration provides school psychologists with a starting point for concrete actions when working with Indigenous students, families, and communities.
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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 | 0.034 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.027 | 0.014 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.009 | 0.014 |
| Research integrity | 0.017 | 0.017 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".