Cite me! Perspectives on coercive citation in reviewing
Bibliographic record
Abstract
Purpose This study builds on previous discussion of an important area for both academics and academic journals – the issue of reviewers inappropriately asking for (or “coercing”) citation of their own work. That situation creates an opportunity for (hopefully a small number of) academics to engage in unethical behaviour, often with the goal of increasing their citation count. This study aims to draw attention to this often-overlooked issue, critically considering potential reviewer motivations and offering possible remedies. Design/methodology/approach This study reviews literature and critically discusses this issue, offering a typology for coercive citation suggestions and sharing previously unpublished commentary from Editors of leading journals. Findings This study provides a typology of reviewer motivations for coercing citations, suggests potential remedies and considers the positive and negative impacts of these suggestions. Originality/value This study identifies an area known from multiple discussions to be important to academics and Editors, where many want changes in journals’ practices. In response, this study provides recommendations for easy changes that would decrease the opportunity for unethical behaviour by reviewers and also, for some journals, improve the quality of reviews.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".