Don't tell it like it is: Preserving collegiality in the summative peer review of teaching
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
While much literature has considered feedback and professional growth in formative peer reviews of teaching, there has been little empirical research conducted on these issues in the context of summative peer reviews. This article explores faculty members’ perceptions of feedback practices in the summative peer review of teaching and reports on their understandings of why constructive feedback is typically non-existent or unspecific in summative reviews. Drawing from interview data with 30 tenure-track professors in a research-intensive Canadian university, the findings indicated that reviewers rarely gave feedback to the candidates, and when they did, comments were typically vague and/or focused on the positive. Feedback, therefore, did not contribute to professional growth in teaching. Faculty members suggested that feedback was limited because of the following: the high-stakes nature of tenure, the demands for research productivity, lack of pedagogical expertise among academics, non-existent criteria for evaluating teaching, and the artificiality of peer reviews. In this article I argue that when it comes to summative reviews, elements of academic culture, especially the value placed on collegiality, shape feedback practices in important ways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.007 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it