Bibliographic record
Abstract
[First paragraph] In 1979, Jean-François Lyotard published the results of a study he was commissioned to write for the Conseil des universités du Québec in which he made the claim that, in a university system devoted to functionalism rather than experimentation, “it is safe to assume that responsibility for [experimentation] will devolve upon extrauniversity networks.” This proclamation may have been shocking to university administrators, who have often equated the university with knowledge as if such a linking were inevitable, but from Lyotard’s perspective of a growing, capitalist-fueled technocracy, and now ours, in which this technocracy has grown in size and nature (with the Internet) along with a university system that has, at all levels, devoted itself both to an increased integration with corporations and structural moves towards adjunct “plebocracies,” the prophecy seems relatively inevitable now. So, the university has more and more ceased to exist as such, as a separate entity, and thus even knowledge produced “within” the university structure cannot be precisely located there.
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 | 0.016 | 0.106 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.021 | 0.018 |
| Insufficient payload (model declined to judge) | 0.028 | 0.019 |
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".