Social Enterprise: A Portrait of the Field
Bibliographic record
Abstract
The Social Enterprise Alliance recently partnered with Community Wealth Ventures and Duke University's Center for the Advancement of Social Entrepreneurship to assess the state of social enterprise in the nonprofit sector in the United States and Canada. The survey effort, which was funded by REDF, was designed to advance the field by identifying trends and best practices among nonprofit organizations engaged in social enterprise activities.For the purposes of the survey, "social enterprise" was defined according to the definition developed by the Social Enterprise Alliance: "An organization or venture (within an organization) that advances a social mission through market-based strategies. These strategies include receiving earned income in direct exchange for a product, service or privilege." Survey respondents were identified from multiple sources, including the partners' databases, and represented a broad range of organization types, sizes and geographic locations. In all, 740 organizations completed the survey. These included organizations that operate a social enterprise, are considering doing so, or are unfamiliar with social enterprise. In this report, we take a deeper look at the survey results, which were originally released in 2009. We also present in-depth profiles of some of the responding organizations.The survey found that the number of social enterprises launched each year has grown steadily since the 1970s, with the most rapid growth occurring during the 1990s and early 2000s. The findings provide empirical data to affirm a trend noted by several researchers and nonprofit leaders in recent years: the blurring of lines between nonprofit and for-profit entities. Nonprofits are becoming more "business-like" in their strategies and incomegenerating activities, while for-profits show an increasing tendency to embrace and advance important social and environmental causes.1Of course, the impact of the 2008-09 recession on social enterprise is yet to be seen and could not be reflected in the survey. The fiscal challenges brought on by the recession might prompt more organizations to consider additional routes for generating added revenues, or it could cause them to delay taking the plunge because of financial uncertainty. Only time, and further research, will tell.Regardless of what happens in the near term, however, the survey results indicate that the trend in recent years has been toward increasing consideration of social enterprise as a route to organizational sustainability and growth.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".