Market University?<i>Universities in the Marketplace: The Commercialization of Higher Education</i> by Derek Bok. Princeton, NJ: Princeton University, 2003. 233 pp. $16.95 (paper). ISBN 0‐691‐12012‐9.<i>Sustaining Change in Universities: Continuities in Case Studies and Concepts</i> by Burton R. Clark. Berkshire: Society for Research into Higher Education and Open University, 2004. 210 pp. $36.95 (paper). ISBN 0‐335‐21590‐4.<i>Knowledge and Money: Research Universities and the Paradox of the Marketplace</i> by Roger L. Geiger. Stanford, CA: Stanford University, 2004. 321 pp. $27.95 (paper). ISBN 0‐8047‐4926‐4.<i>The Future of Higher Education: Rhetoric, Reality, and the Risks of the Market</i> by Frank Newman, Lara Couturier, and Jamie Scurry. San Francisco: Jossey‐Bass, 2004. 284 pp. $33.00 (cloth). ISBN 0‐7879‐6972‐9.<i>Buying In or Selling Out</i> edited by Donald G. Stein. New Brunswick, NJ: Rutgers University, 2004. 188 pp. $25.95 (cloth). ISBN 0‐8135‐3374‐0.
Bibliographic record
Abstract
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.009 |
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".