Bibliographic record
Abstract
In this address, Dr. Curry will discuss the implications of this philosophical disconnect between information professionals and those on university campuses; provide the results of her content analysis research into these silencing actions known broadly as the “heckler’s veto”, results that shed light on the influence of both the Right and the Left political movements; and examine the global cross-border nature of this phenomenon fuelled in part by our new communication technologies.Dans sa conférence, le Dr Curry discutera des implications de ce différend philosophique entre les professionnels de l'information et ceux qui vivent sur les campus universitaires ; elle fournira les résultats de ses recherches en analyse de contenu concernant les actions qui consistent à réduire les gens au silence, actions bien connues sous le nom de « droit de véto du perturbateur » ; résultats qui mettent en lumière la pression de mouvements politiques de droite comme de gauche, et qui examinent aussi la nature transfrontalière et mondiale de ce phénomène, alimenté en partie par nos nouvelles technologies de communication.
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.015 | 0.031 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.060 | 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".