Bibliographic record
Abstract
duty to respect, 204-205; in Indian higher education, 271-273; threats to, 303; protection for, 377-380 academic performance, 160, 344, 387, 407, 411-412 academic research, 11, 106, 247, 256, 294, 320, 393; freedom of, 98; in France, 238-239; industry funding and, 309-310, 320 Act Respecting Academic Freedom in the University Sector (AAFUS), 54,57, 61-65, 70, 73, 161, 175, 185.See also Quebec Act Respecting the Accrediting and Financing of Students' Associations, 71.See also Quebec activism: accusations of, 239; anti-racist, 177; of educators, 108; of students, 180, 184, 190; campus-based, 267 Adivasi, 273.See also casteism administrators, 19, 65, 181, 301; repression against, 223; retaliation by, 325 affirmative action, 267, 271, 275 African universities: academic freedom in, 139-144, 146; and the colonial university, 138-139; Bretton Woods institutions influence on, 136, 141-143; decolonizing the curriculum, 144; epistemic violence on, 146; independent African universities, 139-141; self-censorship, 145; student participation in governance, 143-144.See also colonial university; decolonial education and scholarship; decolonization agreements: adverse impacts of funding agreements, 360; disclosure of, 322; with corporations, 309-310; 314-316; 319, 321-322.See also collective agreements; confidentiality agreements
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.922 | 0.910 |
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".