On being reviewed: from ghosts that haunt in isolation toward connection and unexpected agency
Bibliographic record
Abstract
Our group of early- and mid-career women faculty members in a mid-sized Canadian university examined the peer review process and our experiences of being reviewed. Using post-structural feminist literature, we theorised how subjectivities are shaped by the pressures of neoliberal incursions into university work. The impact of peer review can be severe and feel highly personal. The peer review system contains assumptions that create conditions for misuse: that reviewers have expertise and that notions of quality scholarly work are shared; that they will be supportive and intellectually ethical; and that they will encourage innovation. We engaged with what it feels like to be reviewed through using collaborative autoethnography as a methodology, and narrative and poetic inquiry as data as well as methods of analysis. We found that how a writer received a review depended on the amount of respect and collegiality in the reviewer’s language. Uninformed critical review comments appeared to be particularly damaging. We also found the obscure nature of the process meant that misunderstandings characterised our experiences. Many of us suffered feelings of powerlessness, a homogenisation of writing style, and a decrease in creativity. However, we also found solace and agency in sharing our stories. We shared our experiences within a relational holding space drawing on an ethic of care where well-being flourished, and in which there was an equality of respect, dignity, and mutual concern. We argue this perspective has potential to be applied more broadly to review processes.
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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 | 0.052 | 0.217 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.043 | 0.056 |
| Scholarly communication | 0.030 | 0.017 |
| Open science | 0.004 | 0.025 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".