Multi-Disciplinary Professional Practices: A\nConsumer Welfare Perspective
Bibliographic record
Abstract
Multi-disciplinary professional practices (MDPs) involving lawyers, accountants and otherprofessionals, have been the subject of considerable industrystudyand controversy in Canada and abroad. In this article, the authors evaluate the advantages and disadvantages of MDPs strictly from a consumer welfare perspective. They argue that, although MDP critics' concerns surrounding such issues as solicitor-client privilege, independence, conflicts of interest, and unauthorized practice are valid, they are often overstated and are, in many cases, encountered even today by professionals outside the MDP context. The advantages to consumers of permitting the evolution of such practices would, in any event, significantly outweigh such disadvantages. The authors'analysis provides the background for their specific proposals to facilitate the creation and proliferation of fully-integrated MDPs and an appropriate regulatory framework for such firms emphasizing inter-professional cooperation rather than competition and including inter-professional coordination committees with consumer representation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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; both teacher heads agree on what is shown here.
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".