TIME FOR CHANGE: UNETHICAL HOURLY BILLING IN THE CANADIAN PROFESSION AND WHAT SHOULD BE DONE ABOUT IT
Bibliographic record
Abstract
In the United States hourly billing by lawyers has been demonstrated to lead to both inefficiencies, where clients pay for work done to generate hours rather than results, and dishonesty. While the vast majority of Canadian legal work is billed on an hourly basis, no attempt has been made in Canada to analyze either whether hourly billing leads to the same ethical problems here or whether the regulatory regime governing hourly billing by Canadian lawyers is sufficient. This essay argues that hourly billing leads to inefficiency, the temptation to be dishonest and to dishonesty in fact in the Canadian profession. After outlining the weaknesses in the current regulation of hourly billing - both formal and market - the essay outlines some regulatory reforms which could help to prevent and correct both the specific forms which unethical hourly billing takes and its causes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.043 | 0.062 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.013 | 0.015 |
| 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".