The cost of family law legal services in Canada: a historical and critical analysis of lawyers' business decisions
Bibliographic record
Abstract
This is a study of lawyers' business decisions and the implications of those decisions for access to legal advice and representation in family law. Changes to law office management and the adoption of hourly billing practices, occurred just as family law became a specialized practice area following the enactment of the Divorce Act in 1968. This analysis of the history of pricing legal services in the 1960s and 1970s demonstrates that the high cost of legal services today is the result of choices made by members of the legal profession in the past.Today, one of the central themes in the "access to justice" scholarship in Canada – client-centered justice – glosses over the importance of lawyers' agency. Concurrently, the scholarship on the legal marketplace or the "business of law" primarily addresses large, elite corporate firms, excluding the business practices of many lawyers who provide personal legal services, such as family lawyers.The Canadian organized bar's current approach to legal expense insurance for family law is illustrative of the problem with ignoring the agency of lawyers. The organized bar has not adequately educated lawyers on entering into a relationship with the legal expense insurance industry as an intermediary in billing between lawyer and client. Instead, the focus has been on educating the public to create demand for legal expense insurance.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.030 | 0.011 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| 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".