An Examination of School Psychologists’ Training, Competence, and Needs in Working With Indigenous Students in Nova Scotia
Bibliographic record
Abstract
Indigenous students in Canada typically experience lower educational attainment, graduate at lower rates, and are disproportionately represented on Individual Education Plans compared to their non-Indigenous peers, despite consistent efforts to meet the needs of these students in a culturally responsive way. Many school psychologists report that they do not have the necessary skills and training to work effectively with Indigenous students, meaning that these students might not be adequately supported in schools. Forty-nine Nova Scotia school psychologists completed a survey about their perceptions of their graduate preparation, current knowledge, and knowledge needed to practice effectively with Indigenous students across the APA's six areas of cross-cultural competency. Results indicated that school psychologists felt that their graduate training did not adequately prepare them and that their level of current knowledge was not sufficient to practice effectively with Indigenous students and communities. However, the majority of respondents indicated that they believed it was important to be knowledgeable about Indigenous students' backgrounds and culture, suggesting an openness to learning. Suggestions for training and practice are discussed in the context of the TRC Calls to Action and the CPA accreditation standards, with a focus on transformative education and culturally responsive practices.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".