Junior faculty experiences with informal mentoring
Bibliographic record
Abstract
Mentoring is one way in which new faculty can acquire the skills needed for a successful academic career. Little is known about how informal mentoring is operationalized in an academic setting. This study had two main objectives: (1) to determine if junior faculty identify as having an informal mentor(s) and to describe their informal mentoring relationships; and (2) to identify the areas in which these faculty seek career assistance and advice. The study employed a grounded theory approach. Subjects were recruited from the clinical teaching faculty and were 3-7 years into their first faculty position. Theoretical sampling was employed in which data analysis proceeded along-side data collection, and collection ceased when saturation of themes was reached. Saturation was reached at ten subjects. Data were collected by individual interviews. Four topics recurred: qualities sought in mentors, processes by which guidance is obtained, content of the guidance received and barriers. Faculty obtained guidance in two principal ways: (a) through collegial working relationships; and (b) through discussion with senior clinicians as part of the evaluative system in the department. Participants discussed the degree of mentoring they received in the areas of: career focus, orientation to the organization, transition of role from trainee to faculty and work/nonwork balance. Barriers identified included an evaluative role and conflict of interest on the mentor's part. Junior faculty identify some relationships from which they receive guidance; however, limitations in these relationships result in a lack of mentorship on career direction and on balancing career with personal life.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".