Bibliographic record
Abstract
concerning whether the Community Festivals and Special Events (CFSE) and the Commercial Research Investment (CRIP) Programs, serving Business Improvement Areas (BIAs) and occasionally business associations, and the Economic Development Sector Investment (EDSIP) and the Economic Sponsorship Initiatives (ESI) Programs, serving industry sectors, are fulfilling their stated goals and objectives and to recommend required changes. This report responds to that request. This report reviews these existing programs and recommends the creation of a new Competitiveness, Creativity and Collaboration grant program aligned with the Agenda for Prosperity and the Economic Development, Culture and Tourism Division’s (EDCT) strategic objectives. Staff propose the establishment of a single grant program that will combine the funding of the four existing EDCT programs (CFSE, CRIP, EDSIP and ESI). The new grant program will achieve greater economic development impact, serve to anchor key industry sectors, retain and create jobs, raise public and industry interest and awareness and improve Toronto’s overall business climate. The first grant recipients for the new program would be selected and announced in the
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.484 | 0.305 |
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".