Feature Story: The University announces 2015-16 Board of Governors
Bibliographic record
Abstract
The University of Regina’s 2015-16 Board of Governors includes a new Board Chair, Daniel Kwochka and new Board Vice-Chair, Cathy Warner. Kwochka has served as vice-chair of the Board for one term. Kwochka is a partner with the law firm of McKercher LLP and serves on its Executive Committee. He joined the firm in 1997 and has practised law in Regina since that time. He graduated with a bachelor of arts (advanced) from the University of Regina in 1993 and received a bachelor of laws (distinction) from the University of Saskatchewan in 1996. He articled with the firm of McKercher, McKercher and Whitmore in 1996 and has remained with the firm, now called McKercher LLP, since then as an associate and, later, as a partner. Kwochka holds a Professional Director designation from the Governor Development and Certification program offered by the Ministry of Advanced Education in conjunction with the Johnson-Shoyama Graduate School of Public Policy and Brown Governance Inc.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.150 | 0.059 |
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".