Understanding Supervisory Practices: Commonalities and Differences in Ways of Working with Doctoral Writers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Thesis supervision is a crucial aspect of the doctoral writing experience. While scholarly attention to both doctoral writing and supervisory dynamics is increasing, supervisory support of doctoral students as novice academic writers is still an under-investigated topic. Not having a clear understanding of the way supervisors treat writing gives insufficient insight into a crucial aspect of the doctoral experience. To counter this lack of information about supervision as it pertains to writing, I conducted interviews with seven supervisors who were identified by their doctoral students as a good supervisor of writing. In this paper, I will discuss the practices that unified and those that distinguished these supervisors in their role as supporters of doctoral writing. The supervisors interviewed expressed similar ideas in three areas: reflexivity about academic writing; awareness of variability among doctoral writers; and acceptance of the profound challenges facing doctoral writers. In three other key areas, the supervisors expressed significant differences: attitudes towards the appropriate degree of supervisory support; commitment to writing support as professional development; and facilitation of peer mentoring. These patterns of commonality and difference suggest that good supervisory writing support may allow for significant variations while still drawing upon crucial shared precepts.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
| opus | Metaresearch Domain: Incentives · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
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 | 0.000 | 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 it