The Rise and Decline of State Funded Community Information Centres: A Textually Oriented Discourse Analysis
Bibliographic record
Abstract
Cet article porte sur la methode d'analyse de discours textuellement orientee (TODA), developpee par Norman Fairclough, et de son utilite comme outil analytique approprie pour l'examen de problemes relevant du domaine de la bibliotheconomie et aux sciences de l'information, specifiquement le secteur de l'etude critique des politiques d'information. En tant que tel, le modele a trois paliers de Fairclough est utilise pour realiser une analyse de discours sur un groupe de politiques d'information publiques, afin de decouvrir l'histoire qui se cache derriere l'essor et le declin des centres d'information communautaires subventionnes par l'etat au Canada depuis 1970. En plus de presenter ce modele fertile pour l'analyse de discours en bibliotheconomie et sciences de l'information, cette etude a produit un instrument de recherche adapte du modele de Fairclough, qui est potentiellement reutilisable par des chercheurs travaillant dans d'autres secteurs de ce domaine.
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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 | 0.010 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".