Professional Characteristics of Canadian Counsellors: Results of a National Survey
Bibliographic record
Abstract
With statutory regulation of mental health professions clearly at the forefront in many Canadian jurisdictions, counselling appears to be experiencing internal tensions regarding its vision and direction. The goal of this study was to collect data directly from Canadian counsellors to more clearly define the current practices of counselling in Canada. We developed a web-based survey and invited members of the Canadian Counselling and Psychotherapy Association (CCPA) to respond: 511 (22.9%) completed surveys were returned. Survey data indicate that CCPA members do not believe that the professional identity among Canadian counsellors is clear and coherent and they do not perceive that the profession is widely respected among the public for the services it provides. However, respondents expressed a very high degree of satisfaction with their career decision to become counsellors. The findings have implications for counsellor education as well as the practice of counselling in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".