Delia Opekokew ’77 – the first Indigenous woman to be called in 1979 to the Ontario and Saskatchewan bars – receives honorary Doctor of Laws (LLD) degree from Law Society of Ontario
Bibliographic record
Abstract
TORONTO, ON — The Law Society of Ontario presented a degree of Doctor of Laws, honoris causa (LLD), to distinguished Indigenous advocate Delia Opekokew at its Call to the Bar ceremony today at Roy Thomson Hall in Toronto.\nThe Law Society awards honorary doctorates at Call ceremonies each year to distinguished people in recognition of outstanding achievements in the legal profession, the rule of law, or the cause of justice. Recipients serve as inspirational keynote speakers for the new lawyers attending the ceremonies.\nMs. Opekokew received the honorary LLD in recognition of her advocacy work in furthering the cause of justice for Indigenous People and human rights for all Canadians.\nA member of the Canoe Lake Cree Nation in Saskatchewan, Ms. Opekokew was the first Indigenous woman to be called to the Bars of Ontario (1979), and Saskatchewan (1983). Early in her legal career, she pressed for recognition of the survivors of Residential Schools, one of which she attended for several years. She was also the first woman to run for the leadership of the Assembly of First Nations.\nShe was appointed from 2008-17 as a Deputy Chief Adjudicator on the Independent Assessment Process (IAP), Indian Residential Schools Settlement Agreement (IRSSA). Prior to that, she was an adjudicator on the IAP IRSSA and was also an adjudicator under the Indian Residential Schools Adjudication Process created by the Government of Canada (2004-09). Since 1990, she has practised as a sole practitioner, specializing in Indian treaty rights and Aboriginal law.\nWidely recognized by her peers as a passionate advocate and trailblazer, Ms. Opekokew has received many awards.\nSee full biography online. The Law Society regulates lawyers and paralegals in Ontario in the public interest. The Law Society has a mandate to protect the public interest, to maintain and advance the cause of justice and the rule of law, to facilitate access to justice for the people of Ontario and act in a timely, open and efficient manner.\n -30- \nMedia contact: Susan Tonkin, Senior Communications Advisor, Media Relations, at 416-947-7605 or stonkin@lso.ca
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.042 | 0.007 |
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".