Who is Afraid of the Big Bad Social Constructionists? Or Shedding Light on the Unpardonable Whiteness of the Canadian Legal Profession
Bibliographic record
Abstract
This article considers the lack of racial diversity in the legal profession, which is lower than other comparable professions. The author focuses on accessibility to the legal profession and entry into the practice. Historically, access was limited, and sometimes prohibited, by discriminatory social and statutory barriers. Tuition for post-secondary education is now a central barrier that increasingly divides along racial lines, due to the nexus between class and race. Despite the attention given to the problem of lack of racial diversity in the legal field through reports, task forces, surveys, and so forth, there is still much progress needed in order to ensure that the diversity ofthe profession reflects the makeup of the country's population. The author advocates the elimination of barriers to legal education and subsequent entry into the profession through cooperative initiatives between schools, firms, legal associations, and community organizations in order to increase racial equity and diversity within Canada’s legal profession.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.026 | 0.039 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".