Social Enterprises in OECD Member Countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This chapter focuses on the emergence of financial instruments and enabling environments for social enterprises in selected OECD countries, with particular focus on Western European countries, Canada and the United States, and possible strategies for supporting their development in Eastern European Countries. As social enterprises continue to draw the attention of national governments and local authorities alike in the fight against unemployment and social exclusion, they are also being embraced by civil society as a way of addressing unmet needs in a sustainable manner. Social enterprises are emerging in numerous sectors producing goods and services, thereby increasingly demonstrating their capacity as economic actors. They are similarly considered as key to socio-economic transformation in transitional economies. As the chapter suggests, the incompatibility of an existing investment framework, tied to outmoded and fixed categories that do not correspond to the new reality of social enterprises and their investment needs, requires cultural adaptation of the financial, legal, accounting and policy communities internationally to this new reality before the appropriate and enabling tools can be designed. For social finance to become sustainable finance, an integrated approach has to be adopted that is distinct from traditional capital markets. In conclusion, and regardless of the breadth of instruments available, the real potential of social enterprises will only be realised if they are integrated into a systemic approach to social exclusion, labour market transformation, and territorial (place-based) socio-economic development strategies that requires innovative public policy.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 it