Holding Firm: Power, Push-Back, and Opportunities in Navigating the Liminal Space of Critical Qualitative Health Research
Bibliographic record
Abstract
Critical qualitative health researchers typically occupy and navigate liminal academic spaces and statuses, with one foot planted in the arts and social sciences and the other in biomedical science. We are at once marginalized and empowered, and this liminality presents both challenges and opportunities. In this article, we draw on our experiences of being (often the lone) critical qualitative health scholars on thesis advisory committees and dissertation examinations, as well as our experiences of publishing and securing funding, to illuminate how power and knowledge relations create conditions that shape the nature of our roles. We share strategies we have developed for standing our theoretical and methodological ground. We discuss how we use the power of our liminality to hold firm, push back, and push forward, to ensure that critical qualitative research is not further relegated to the margins and its quality and integrity sustained.
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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 | 0.291 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.007 |
| 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".