Social Enterprise, Law and Legal Education
Bibliographic record
Abstract
In this brief essay, we explore the relationship between law and social enterprise. Is social enterprise, like the “corporation,” a legal construct, or is it a term used to capture an emerging set of practices by existing entities—for example, where registered charities set up a separate structure to generate revenues which then fund the charitable activities. An organization that has undertaken such practices is the well-known Canadian charity, “Me to We,” which, while focused on development activities in sub-Saharan Africa, also has a revenue generating operation selling fair trade T-shirts and other goods. In describing this relationship, Me to We’s website declared:\nME to WE social enterprise combines best business practices with increasing social awareness. Our commitment to help improve cultural, community, economic and environmental outcomes is at the centre of our business. Every ME to WE product sold makes a direct, measurable impact in a WE Charity community overseas, empowering them to build a better future.\nOther approaches to social enterprise suggest a new legal hybrid is emerging which combines elements of for-profit business with elements of NGO social purposes. Whether a new legal structure emerges, or existing structures are adapted, a host of important legal questions follow. As designation as a social enterprise may have tax and regulatory implications, how is social enterprise to be defined? Where public benefits are created for social enterprise, such as Ontario’s “Social Enterprise Strategy” and “Social Enterprise Demonstration Fund” which boasts a population of 10,000 Social Enterprises in the province, who counts as a social enterprise and why? Is this jurisdictional boundary a function of statutory interpretation, policy, or the operational discretion of a public agency of funding body?
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.034 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".