PERCEPTIONS OF GRADUATE SUPERVISION: RELATIONSHIPS WITH TIME OF REFLECTION AND POST-SECONDARY CLIMATE
Bibliographic record
Abstract
This paper discusses the similarities and differences between Canadian doctoral students and new faculty members regarding their experiences with and perceptions of their graduate supervisors and mentoring. Participants’ responses were considered in light of the current post-secondary culture that emphasizes increased productivity and accountability of faculty members and the student as customer (e.g., Turk, 2000). An examination of survey and interview responses from participants showed that whereas both groups valued supervision that includes both career and psychosocial functions of mentoring (Kram, 1983), doctoral students tended to place more emphasis on the psychosocial functions than did the new faculty. In addition, although, in general, both groups gave more favourable ratings of their supervisors for career as opposed to psychosocial functions, new faculty members were more satisfied with their supervisors and rated their supervisors higher on most mentoring functions. These differences between groups were considered in light of universities’ adoption of a managerial, audit culture (e.g., Cribb & Gewirtz, 2006) that encourages students to perceive themselves as consumers and requires faculty to meet competing demands on their skills and time.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".