Collectively Dreaming Toward Indigenized School Psychology Education and Training
Bibliographic record
Abstract
Indigenous Peoples comprise a significant portion of the population whose mental health needs must be appropriately addressed, and schools are important contexts for this service provision. The author presents findings from a culturally-grounded, strengths-based, qualitative, Two-Eyed Seeing study that engaged with current and previous Indigenous graduate students from Canadian mainstream and Indigenized counseling psychology programs to explore their graduate school experience and dream for the future of psychological education and training. Community-led analysis with aspects of qualitative thematic analysis guided a collective results narrative. Eight findings emerged including: (1) the importance of relationality in education and training; (2) the significance of experiential learning (i.e., land and art-based, ceremonial, interpersonal relations); (3) diversity in knowledge sharers and inclusion of elders in psychology education; (4) critical decision-making about cohort member inclusion (i.e., all indigenous cohorts vs. mixed); (5) mandatory Indigenous pre-requisite courses; (6) cultural humility; (7) teachings about how to be a good person rather than how to be a good counselor; and (8) interviews for program entry. These findings are discussed in the context of future practice, intervention, education, and training of school, educational, counseling, and clinical psychologists, as well as pedagogical and curricular programmatic changes in multi-educational levels (i.e., K-12 and post-secondary). Considerations and areas of future research are discussed.
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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 | 0.006 | 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 | 0.018 | 0.023 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".