Development of Peer Advisors' Competencies and Career Clarity in the St. George Career Centre at the University of Toronto
Bibliographic record
Abstract
Undertaken in Fall 2015, this case study of 14 Peer Career Advisors working at the St. George Career Centre in the University of Toronto was intended to determine participants’ perspectives of the development of their competencies and career clarity through their roles, as well as the experiences supports available through the Career Centre that influenced development, and any additional supports that would enhance development. Theoretical underpinnings include Chickering and Reisser’s vectors of development, Super et. al.’s life stages theory of career development, and Kolb’s theory of experiential learning. Results of the study demonstrated that all participants perceived development through their roles, the majority reporting competency development and specifically advising skills. Participants reported training, professional development tasks, and opportunities for feedback contributed to development. Perceived barriers to development included lack of free time, the need to balance multiple responsibilities/priorities, and lack of both job-related and self-knowledge.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".