Uncivil advocacy: An intensifying spotlight on incivility in advocacy cannot be ignored [online]
Bibliographic record
Abstract
Early in 2015 a Canadian court referred to an "increasing concern over the last number of years that the conduct of lawyers is becoming less and less civil - both inside and outside the courtroom".1 The court pondered the drivers for this 'increase in incivility' in the context of advocacy, including vis-a.-vis the opposing lawyer, client or witnesses, and also the Bench. One driver, it surmised, could be demands by clients who, completely unfamiliar with what actually constitutes effective advocacy, believe that an aggressive lawyer is an effective lawyer. Competition for legal work may prompt aggressive advocacy in the belief that clients desire an 'attack dog' . The court identified a second, related driver, namely the image of lawyers in television shows, and in other media, where actors portray lawyers in a fashion unrestrained by any need to represent reality and without concern for the reputation of the legal system.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.036 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".