A decolonial critique of metaphysics in counselling psychology education
Bibliographic record
Abstract
How can we listen to Indigenous Knowledges about our relationships with land? This dissertation offers three examples of how Canadian counsellor education and counselling psychology programs can be truly open to the ecological and theoretical gifts that Indigenous Knowledges offer academia—open in ways that align with our core values of listening, respect, relationality, healing, and holistic well-being. Each of the three projects provokes our assumptions about the relationship between ourselves and the land. The first project challenges Western disciplinary histories and asks us to listen to the history of education that has had its being in this land for millennia. The second challenges our science of intelligence and invites us to listen to land-based, experiential realities of cognition. The third investigates nonindigenous counselling students' ways of being in places of schooling where their worldview does not match their institution's. It challenges the assumption that students' minds are simply broadened by coming to university, and opens us up to students' existing relationships to land through the lens of Indigenous Knowledges. This dissertation shows that there is room for, strategic places of insertion of, and student willingness to absorb decolonized curriculum and pedagogy in Canadian counsellor education and Canadian counselling psychology generally. Indigenous Knowledges benefit the field by broadening the conceptions of humanity we use to educate our students and clients, and by deepening our stories of what counselling education is and has been.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.162 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".