Book Review: Bar Codes: Women in the Legal Profession, by Jean McKenzie Leiper
Bibliographic record
Abstract
s study of women in the legal profession examines the struggles faced by the "first wave" 3 of women lawyers in Ontario.Using Shakespeare's Portia from the Merchant of Venice as a unifying metaphor for her analysis and conclusions, Leiper demonstrates how the robes of lawyers remain "ill-fitting and inadequate" 4 for most women employed "in a culture bound by men's rules." 5 "Unwritten" and heavily "guarded" "codes" 6 of conduct pertaining to the need for a lawyer's open-ended availability have proven resistant to change.The traditional, one-dimensional male paradigm, requiring continued and unfettered devotion to work on a full-time basis, as well as the ability to be freed from personal responsibilities at will, remains the norm.Leiper concludes that this aspect of the "gentleman's ''7 profession has not changed in any meaningful manner despite years of research by academics, bar associations, and law societies, and despite many.professed commitments and policies designed to promote change.Those who cannot or will not fit within this model must alter their career paths or accept being relegated to less powerful positions within the profession.Leiper's conclusions are based upon her study of 110 women lawyers of different ages and from diverse social and cultural backgrounds who practise law across Ontario in many areas of practice.Leiper followed the careers of these women from 1994 to 2002 and used personal interviews, as well as follow-up questionnaires and e-mails, to / [Bar Codes].2Sole Practitioner.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.018 | 0.011 |
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".