Bibliographic record
Abstract
In October 2007, the Vice-President and Provost announced the formation of a Task Force on Outreach Activities at the University of Toronto. The objectives, as set out in the terms of reference attached to the end of this document (Appendix 1), directed the members of the group to assess and make recommendations regarding the scope of our existing programs; the ways we measure their success; the internal and external relationships forged by our existing programs; and participant engagement. The Task Force met from November 2007 through to March 2008, considering outreach documentation about programs offered at U of T, at comparator universities, and within the broader community. It heard representations from a number of guests including engaged students, U of T equity officers, staff from the Transitional Year Program and the Millie Rotman Shime Academic Bridging Program, and representatives involved in outreach initiatives offered by our professional faculties. Its chair attended a Quality Networks for Universities conference on community partnerships and an Association of American Colleges and Universities meeting on Educating for Social Responsibility for further background information. Submissions were invited from interested parties. A
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.217 | 0.077 |
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".