The Power of Feedback to Foster Wellbeing, Relatedness, and Goal Achievement in Mentoring Relationships
Bibliographic record
Abstract
Abstract Mentoring programs and processes are diversely conceptualized and enacted. Broadly speaking, mentoring provides valuable onboarding supports, promotes psychosocial functioning, and fosters wellbeing. This chapter examines the online reflections of graduate students who studied how giving and receiving feedback influenced wellbeing in mentoring relationships. The four key findings show that: purposeful, constructive feedback builds healthy mentoring relationships, mentoring is emotionally charged and linked with wellbeing; feedback delivery affects wellbeing, yet mentors need time to understand and develop effective feedback skills, and scholarship can help with the understanding of and developing mentor-mentee relationships. With a dearth of professional learning and development focused on how to give and receive feedback effectively, this topic is essential for all mentoring programs and courses, with particular attention to how purposeful constructive feedback practices can establish trust, support, and care in mentoring relationships.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".