Mentorship as a Career Intervention: An Evaluation of a Peer-Mentoring Program with Canadian University Psychology Students
Bibliographic record
Abstract
This study evaluated the effectiveness of the Canadian Psychological Association (CPA) Student Mentorship Program, a formal peer-mentoring program for undergraduate students (mentees) and graduate students (mentors) studying psychology in Canada. Previous researchers have not sufficiently examined the effectiveness of formal peer-mentoring programs, particularly within the psychology discipline in higher education settings. The purpose of this investigation was to explore the program’s effectiveness as a career intervention, including its acceptability, feasibility, outcomes, strengths, and limitations. One hundred and seventy-eight students participated in the program and data was collected at three time points (at baseline, three and six months). Descriptive and inferential statistics were obtained, in addition to minimally inductive content analyses for open-ended items. Results indicated that most mentors (63%) and mentees (58%) experienced the program as effective to highly effective, with 100% of participants supporting of the continuation of the program. Overall, 86% of mentors and 63% of mentees reported that participation in the program was moderately to strongly related to the achievement of their career goals. Program strengths and limitations were identified which reinforce aspects of the program that have served participants well, in addition to areas which should be improved for future iterations of the peer-mentoring program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".