Lawyers as Gatekeepers, Investors and Advisors: An Analysis of Innovation in Legal Fee Arrangements (and Implications for the Lawyer-Client Relationship and the Public Interest)
Bibliographic record
Abstract
Silicon Valley law firms were among the first to experiment in taking stock in their technology start-up clients. Law firms in other financial centers in the United States have also begun to accept equity in their high-tech clients, as have several Canadian law firms. Even the most conservative law firms in England have accepted accepting small equity stakes in their clients, and the trend is spreading throughout Europe. This article critically analyzes the practice of lawyers taking equity in their clients as compensation for rendering legal services. The article concludes that equity billing can provide significant private benefits to law firms and clients, as well as indirect public benefits. The article also concludes that equity billing can be usefully analogized to contingency fee arrangements: equity billing is to start-up clients and corporate legal work what contingency fee arrangements are to impecunious litigants and access to the courts. The article then addresses ethical issues raised by equity billing. Can equity billing be reconciled with ethical rules that lawyers? fees be reasonable? Can equity billing be reconciled with concerns about conflicts between a client?s best interests and the lawyer?s self-interest? Equity billing also raises a concern that the lawyer?s role as guardian of the public interest, particularly in the context of public securities markets, will be undermined. This article applies the economic theory of gatekeeping and concludes that equity billing may impose externalities on third parties such as retail investors who rely on issuers? lawyers to ensure compliance with securities laws. The article concludes that a case cannot be made for prohibiting equity billing or capping the amount of equity that a lawyer can take in a client, and that the most appropriate form of regulation is heightened disclosure of equity billing arrangements, coupled with letting existing ethical rules, fiduciary principles and market forces regulate.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".