Bibliographic record
Abstract
This paper examines the 33 year-long jurisdictional dispute between immigration lawyers and immigration consultants over the right to practice immigration law in Canada. Immigration consultants began to play a role in the immigration law field of practice in the 1980s. Their entry into this field of practice has not gone unnoticed by immigration lawyers. The paper focuses on two moments in this jurisdictional dispute; the events surrounding the Supreme Courts' 2001 decision in the case of the Law Society of British Columbia v Mangat and the 2017 hearings of the Standing Committee on Citizenship and Immigration. Using an ecological framework to understanding the professions, and professional boundary disputes, this paper examines the reasons why the profession of law has not been able to exert monopolistic closure and prevent immigration consultants impinging on one of their traditional fields of practice. Part of the explanation, I suggest, is that immigration lawyers did not speak with one voice about immigration consultants at the 2017 Standing Committee hearings. The Canadian Bar Association's preferred settlement outcome was for the state to prevent immigration consultants from practicing immigration law. Other lawyers who appeared before the Committee advocated a boundary blurring outcome that would allow immigration consultants to practice immigration law, albeit under somewhat more restricted conditions than were then in place. The state rejected a 'full and final settlement' in favor of lawyers and eventually adopted a boundary 'blurring settlement' outcome to this jurisdictional dispute.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.037 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".