Rethinking reflexivity, replicability and rigour in qualitative research
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
This commentary re-examines recent proposals to define quality in qualitative research through a singular unifying framework, situating them alongside historical and ongoing debates in qualitative methodology. By juxtaposing different traditions, this piece highlights areas of tension between procedural notions of rigour and interpretive approaches that emphasise the co-constructed, context-bound nature of meaning. The discussion argues that quality in qualitative research cannot be captured by a single metric or universal rule. Reflexive approaches resist rigid frameworks, instead favouring a situational and evolving engagement with meaning. While efforts to promote transparency and accountability in qualitative research are valuable, researchers should adopt methodological criteria aligned with their epistemological commitments. We argue that qualitative research can be considered rigorous insofar as it is deeply reflective, explicitly contextualised and transparent about its interpretive manoeuvres.
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 | 0.130 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it