Social Enterprises Models in Canada: Ontario
Bibliographic record
Abstract
The objective of this article is to examine social enterprises in Ontario, Canada, as part of the “Social Enterprises Models in Canada” research of the International Comparative Social Enterprise Models (ICSEM) Project. The report presents an analysis of the historical, contextual, and conceptual understanding of social enterprises in Ontario. Five cases studies illustrate social enterprise models, and the article then presents the main institutions in Ontario related to social enterprises, describing legal framework, public policies, university institutions, networks, spaces, and funding agencies and programs. Dans le cadre du projet Modèles d’entreprises sociales au Canada de l’International Comparative Social Enterprise Models (ICSEM), l’objectif du présent article est d’examiner les entreprises sociales en Ontario, Canada. Le rapport présente une analyse historique, contextuelle et conceptuelle pour comprendre les entreprises sociales en Ontario. Cinq études de cas illustrent les modèles d’entreprises sociales. Les principales institutions liées aux entreprises sociales en Ontario, tel que le cadre législatif, les politiques publiques, les établissements universitaires, les réseaux, les espaces, les organismes de financement et les programmes, sont décrites.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".