Bibliographic record
Abstract
The procedures commonly employed for quality assurance in higher education are designed as if the endeavour were a technical process, whereas it may be more useful to view it as a political process. For example, quality assurance requires making choices among competing conceptions of quality, and in so doing privileges some interests over others. Moreover, some stakeholders tend to be given a greater voice than others in the design and implementation of quality assurance. The author concludes that rather than denying the political nature of quality assurance, it would be better to accept Morley’s claim that quality assurance is “a socially constructed domain of power”, and design procedures for it in a way that is appropriate for a political process. It is suggested that employing the “responsive model” of evaluation could make quality assurance more effective in improving educational quality. In the responsive model, evaluation is deemed to be a collaborative process that starts with the claims, concerns and issues put forth by all stakeholders.
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 | 0.035 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.042 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".