Constructing Research Quality: On the Performativity of the COREQ Checklist
Bibliographic record
Abstract
The Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist was designed to enhance quality in the reporting of interview and focus group studies, and it is widely endorsed by journals and publishers. However, it has also been heavily critiqued for its design and application in qualitative health research communities. In this article, we conduct detailed critical text analyses of eight articles and their accompanying self-reported COREQ responses and discuss the performative force of the checklist on the appearance of research quality. The analyses of authors' rhetorical strategies in articles and checklist responses indicated that they sometimes provide misleading, inconsistent, or excessive information, prioritizing checklist completion over substantive engagement with quality principles. While intended to standardize reporting, COREQ's rigid structure often led to overcompliance or inappropriate responses from authors, who strived to meet its criteria, even when they were irrelevant or unsuitable. This "overobedience" reflects a desire to maintain credibility and avoid scrutiny, yet it undermines the depth and rigor of qualitative research. COREQ is an epistemic device, shaping researcher practices and identities beyond its stated purpose, and while COREQ aims to enhance accountability, it perpetuates epistemic dominance, eroding authenticity and critical reflection in qualitative research, ultimately exacerbating the very problems it seeks to solve.
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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 | 0.480 | 0.183 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.005 |
| 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; both teacher heads agree on what is shown here.
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".