Committee Members’ Perspectives on Admissions to Canadian Master’s-Level Counselling Programs: Personal Qualities and Gatekeeping Considerations
Bibliographic record
Abstract
Counsellor personal qualities play a role in admission decisions and counsellor efficacy. However, personal qualities have been sparsely investigated regarding admissions to counselling programs in Canada and internationally. Also, counsellor personal qualities lack clarity for adequate assessment at any regulatory stage. Our preliminary study explored counsellor personal qualities according to Canadian counsellor educators. It explored how these educators represent and reflect upon admissions at their institutions. Six Canadian counsellor educators participated in semi-structured individual interviews. Results demonstrated that personal qualities deemed important by participants for both admissions and practice were largely consistent with the current literature. Most participants preferred that personal qualities be assessed during admissions, typically through interviews. Overall, admissions processes appeared to be inherently subjective regardless of efforts at objectivity. Implications of the study 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 | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".