“Praise in Public; Criticize in Private”: Unwritable Assessment Comments and the Performance Information That Resists Being Written
Bibliographic record
Abstract
PURPOSE: Written assessment comments are needed to archive feedback and inform decisions. Regrettably, comments are often impoverished, leaving performance-relevant information undocumented. Research has focused on content and supervisor's ability and motivation to write it but has not sufficiently examined how well the undocumented information lends itself to being written as comments. Because missing information threatens the validity of assessment processes, this study examined the performance information that resists being written. METHOD: Two sequential data collection methods and multiple elicitation techniques were used to triangulate unwritten assessment comments. Between November 2022 and January 2023, physicians in Canada were recruited by email and social media to describe experiences with wanting to convey assessment information but feeling unable to express it in writing. Fifty supervisors shared examples via survey. From January to May 2023, a subset of 13 participants were then interviewed to further explain what information resisted being written and why it seemed impossible to express in writing and to write comments in response to a video prompt or for their own "unwritable" example. Constructivist grounded theory guided data collection and analysis. RESULTS: Not all performance-relevant information was equally writable. Information resisted being written as assessment comments when it would require an essay to be expressed in writing, belonged in a conversation and not in writing, or was potentially irrelevant and unverifiable. In particular, disclosing sensitive information discussed in a feedback conversation required extensive recoding to protect the learner and supervisor-learner relationship. CONCLUSIONS: When documenting performance information as written comments is viewed as an act of disclosure, it becomes clear why supervisors may feel compelled to leave some comments unwritten. Although supervisors can be supported in writing better assessment comments, their failure to write invites a reexamination of expectations for documenting feedback and performance information as written comments on assessment forms.
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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 | 0.046 | 0.238 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".