Rightsizing Regulation: The Competition Act, 1975–2005
Bibliographic record
Abstract
Résumé Cet article examine les changements au niveau de la réglementation des crimes commerciaux dans le domaine de la loi relative à la concurrence déloyale et aux pratiques commerciales trompeuses. L'auteur se penche, plus particulièrement, sur les politiques et les applications deLa Loi relative aux enquêtes sur les coalitionset de laLoi sur la concurrencede 1975 à 2005. Cette période fut marquée par des changements importants dans la régulation juridique: les discours, les pratiques et les politiques keynésiens de l'État providence furent remplacés par ceux de l'État régulateur néolibéral. Le Bureau de la concurrence fut un acteur clé dans cette transition par laquelle les politiques sur la concurrence devinrent un mécanisme essentiel de régulation primaire de l'État moderne. Cet article analyse les documents relatifs à l'application des lois, les rapports annuels ainsi que d'autres documents du Bureau de la concurrence afin de démontrer, d'une part, comment les priorités et les pratiques ont changé et, d'autre part, comment ces changements régulatoires sont liés au remplacement des politiques économiques keynésiennes par celles de l'Élat néolibéral.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".