Bibliographic record
Abstract
Over the last decades, qualitative researchers from the global south have questioned the dominance of the Anglo-American core and the current divide between the core and periphery. Nevertheless, it is unclear how to disrupt the divide. This article advances this endeavour by demonstrating the interplay between Anglo-American domination and a local hegemonic discourse that has perpetuated the core–periphery divide and hindered the development of critical qualitative research (QR) in the periphery. The author conceptualizes the periphery as an incubator that nurtures locally grounded and globally informed qualitative researchers. This demands interrogating the interplay between core domination and local hegemony. Doing so lays the foundation for qualitative researchers in the periphery to explore, and eventually articulate, decentred methodologies and locally situated epistemologies on a globalized platform. Using two case studies of QR conducted in China, the article examines the practices and politics of doing (critical) QR in contemporary China. It discusses methodological and epistemological issues pertinent to decentring QR in a global era.
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.
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 | 0.047 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.015 | 0.027 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".