Illusions of Control? The Extension of New Public Management Through Corporate Governance Regulation
Bibliographic record
Abstract
Abstract: This study investigates the process of adoption of a new governance regulation in the public sector. The empirical setting of this paper is the adoption by the Québec government of regulations regarding the role of boards for 24 government enterprises. Building on a Latourian framework, the investigation relies on the analysis of parliamentary debates, commission hearings, and interviews with key participants. Plans to ‘improve’ governance were initially presented in generic formats in electoral promises of reform. Plans were then promoted through the construction of linkages with global and local scandals, as well as references to discourses about increasing distrust of public institutions and the absence of markets as a means to control behaviours. My analysis suggests that regulation offered as a ‘modernization of governance’ and viewed as an irreversible phenomenon to which one cannot oppose, may be an illusion of control within the public sector. Ideals of modernized governance continue to spread in society through their construction in ‘laboratories’ (e.g., commission hearings), where effectiveness in various jurisdictions is assumed and not questioned by governance experts, accountants and their technologies.
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 | 0.030 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.082 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".