The Preclusion of Nonlawyer Ownership of Law Firms: Protecting the Interest of Clients or Protecting the Interest of Lawyers?
Bibliographic record
Abstract
For the third time in as many decades, lawyers in the United States have sullied the notion of nonlawyer ownership of law firms. The most recent examination of alternative law practice structures was undertaken by Ethics 20/20, a Commission created by the American Bar Association [ABA] to conduct a plenary assessment of the ABA Rules of Professional Conduct and related ABA policies. A Working Group was formed which considered whether clients could be better served if law practice entities were restructured. To this end, issues were formulated and different law practice configurations were proposed, about which the public and members of the legal profession were invited to comment. Receiving mixed reviews, Ethics 20/20 decided not to put the matter of nonlawyer ownership of law practices before the ABA House of Delegates in 2012 and 2013, when revisions to the ABA Rules were considered.Precluding nonlawyer ownership of law firms has been the majority rule in the United States for almost a century. With the exception of the District of Columbia, the states do not allow nonlawyers to own interests in law firms. However, this is not the case in the rest of the world. A number of countries allow nonlawyer ownership of legal practice entities, as well as other practice formulations where legal services can be a component part of another business. Many feel formulations such as these better serve the public and make legal practitioners more competitive, especially in the international marketplace. All this notwithstanding, United States critics of nonlawyer ownership claim that such formulations are unnecessary, will threaten the core values of the profession, and will undermine the profession by leading to loss of self-regulation. Looking at the experience of the District of Columbia, as well as countries such as Australia, Canada and England & Wales, this doesn’t seem to be the case.An examination of the opposition to nonlawyer ownership of legal practices reveals that the primary focus in the United States has been directed toward the well being of the legal profession, rather than toward the well being of the community at large. Those who seek to keep the status quo don’t even want to have the discussion. This reluctance comes from lawyers wanting to protect themselves rather than concern for clients and the public.
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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 | 0.032 | 0.088 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.051 |
| Scholarly communication | 0.020 | 0.029 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.020 | 0.023 |
| Insufficient payload (model declined to judge) | 0.005 | 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".