Shifting Values and Voices: An Exploration in Holistic Mentorship Evaluation
Bibliographic record
Abstract
The roles in traditional mentoring dyads are well known across both academic and professional contexts (Dawson, 2014). Despite the universality of these relationships, the way mentorship is evaluated in these relationships is fractured. Evaluation is limited to singular voices, singular points in time and simplified metrics to capture the journey and the unique experience of mentorship. These gaps push mentorship evaluation to try to encapsulate mentorship as a generalizable experience to satisfy metrics rather than acknowledging the dynamic complexity of these relationships. An exploration of current mentorship evaluation within the literature will highlight current limitations. These limitations allowed the authors to propose a new Co-Analysis model for evaluation that centers on shifting mentorship towards the values of partnership, flexibility, and holistic assessment. The model not only provides a universal pathway to improve any individual mentoring relationship, but also the opportunity for new voices to shape our understanding in future literature.
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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 | 0.101 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.024 | 0.022 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.003 | 0.005 |
| 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".