A Model for the Education of Career Practitioners in Canada
Bibliographic record
Abstract
Most professions dictate the educational levels needed, first to access and then to advance within them. That is not the case for the relatively young field of career development in Canada, where such requirements are absent everywhere but in the Province of Québec. The following article presents an educational framework developed through a Canada-wide consultative process that proposed educational benchmarks for various scopes of career development practice. Five core functions were identified and defined: career advising, career educating, career counselling, career coaching, and career consulting. Moreover, several leadership functions integral to the field’s performance and advancement were identified: innovation, education, supervision of practice, systemic change, and management. Ultimately, the framework will help promote quality of service, professional identity, and professionalism in the career development field. Recommended next steps include generating a wellintegrated curriculum map to promote program and individual practitioner development.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".