Qualitative Inquiry in the Public Sphere
Bibliographic record
Abstract
"Qualitative Inquiry in the Public Sphere examines the relationships between public scholarship, the research marketplace, and the politics of higher education.?It is written from the perspective that higher education is under attack from multiple sides, both political and economic; that academics reside in a precarious position, one fraught with accountability metrics, funding pressures, and spiralling bureaucracy; and that scientific knowledge itself is increasingly contentious in public. These internal and external pressures have fundamentally transformed the public sphere of higher education from one of rational public discourse by and for the public good to one of private market relations and strategic research decisions. In turn, these transformations have fundamentally altered what it means to be a productive scholar within this spacealtered what it means to be a public researcher in this space. Leading international voices from the United States, Canada, Germany, the United Kingdom, and Norway collectively present a forceful rebuke to such developments, raising a clarion call to action on topics ranging from scholarly publishing, audit culture, and the privatization of public knowledge to Indigenous, arts-based, and collaborative research methods. Qualitative Inquiry in the Public Sphere is a must-read for faculty and students alike interested in the politics of being a public researcherof conducting research in and influencing dialogue in the public sphere."--Provided by publisher
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 | 0.062 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".