Bibliographic record
Abstract
In Canada and around the world governments are granting an increasing number of professionals and other occupations in the service sector the right to self-governance and self-regulation or the delegation of authority that the state would normally hold. Self-regulation has become the preferred method of monitoring professional competence, standard setting, certification and the development of ethical codes of practice for a broad range of traditional professionals such as doctors, lawyers, real estate agents, insurance agents, human resource managers and many more. There are numerous advantages to self-regulation for professionals or an occupation aspiring towards professional status. The mere fact of self-regulation enhances the credibility and standing of an occupation and its members in the eyes of the public. Rulemaking or rule-enforcing powers grant autonomy and self-determination to professionals, cementing their status within society and providing them with influence over public policy and decision-making. Self-regulation can also assist a group in developing rules that are more responsive to the complex issues within a profession such as the avoidance of conflicts and ensuring that the current needs of clients are being adequately addressed. From the perspective of the state, self-regulation has the advantage of reducing the costs of regulation. The delegation ranges from a complete transfer of rulemaking and rule-enforcing authority from the state to the self-regulator, or through a partial delegation of regulatory powers, with the government able to provide some oversight. Self-regulation can be a smarter solution when a state-organized regulator lacks the financial means or political willpower to regulate in the best interests of the public and at the lowest cost possible.While the advantages of self-regulation are generally understood by governments and the professions, the downside of this form of regulation is less understood and often complicated by the nature of the interests at play. In this Commentary, I examine the role of self-regulators in Canada and some of the issues that can arise when self-regulating organizations take on policy and other decision-making roles traditionally held by governments. This Commentaryexplores examples of various policy decisions and actions taken by self-regulated organizations that have had or could have an impact on private businesses and the quality of service and representation afforded to the public generally and clients of professional services specifically. I recommend that governments tighten the procedural and substantive rules that affect the operation and scope of powers of self-regulatory and other organizations delegated authority by legislation.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".