Giving thanks: the relational context of gratitude in postgraduate supervision
Bibliographic record
Abstract
Successful postgraduate supervision is often dependent upon the quality of the relationship between postgraduates and their supervisors. This article reports on two studies that focus on grateful affect and grateful expression within low‐ and high‐trust postgraduate–supervisor working relationships. In Study 1, a sample of Canadian postgraduates and supervisors was interviewed to explore the consequences of expressed gratitude and identify supervisory behaviors for which postgraduates are grateful. In Study 2, a sample of Australian postgraduates was surveyed. Results showed that perceptions of supervisors’ altruism and the perceived value of supervisors’ behaviors were positively related to the grateful affect felt by postgraduates in low‐trust working relationships. In contrast, perceptions of supervisors’ altruism and the perceived value of supervisors’ behaviors were not related to grateful affect in high‐trust working relationships. Implications for theory and practice are discussed.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| 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".