Divisional Space Review and Development of a Master Plan Abbreviated Report: Executive Summary, Recommendations, Observations, Recommended Actions
Bibliographic record
Abstract
“Today as we approach our second centennial, the University of Toronto is respected as one of the foremost research-intensive universities in the world... Even as a publicly supported institution with constrained resources, we have been able to rival both the great private universities of the United States and the ancient public universities of Britain in the quantity and quality of our research and scholarship.- President David Naylor, U of T Magazine, Winter 2009EXECUTIVE SUMMARY The Space Review Committee was established by Dean Cristina Amon in September, 2008. The report is intentionally presented in three distinct and cohesive sections, namely Sections A, B and C, to include specific observations from the undergraduate and graduate representatives respectively serving on the Committee. Both representatives sought out input through discussion and interaction with their respective peer groups in the preparation of these representative observations. It should be noted however that no formal student town-hall meetings were held and that both reports received the full support of the Committee for the Divisional Space Review and Development of a Master Plan. Section A provides valuable insight of the needs of the undergraduate student body which have been assembled with input from student colleagues by Mr. Jimmy Lu. Section B provides a
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 | 0.041 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.056 | 0.063 |
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".