Politics, ecologies and professional regulation: The case of British Columbia's Professional Governance Act
Bibliographic record
Abstract
A variety of theories have been proposed to explain why states pass legislation to regulate professional groups, and why, more recently, they have acted to curtail professional privileges. While these theories have drawn attention to the importance of power dynamics and public protection, among other factors, the role of political interests has been downplayed. This article builds on ecological theory to argue that, with some modifications, the theory illuminates the centrality of state-profession relations and politics to regulatory change. The theory is applied to a case study of regulatory change in British Columbia, Canada impacting resources-sector professions, with particular attention to the controversies and political considerations that shaped reform. The case study suggests that when the political and professions ecologies are overlapping and symbiotic, as they were in BC, a challenge in the political ecology can implicate professions, prompting a solution that brings change within both ecologies.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.012 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| 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".