Measuring the Size, Scope & Scale of the Social Enterprise Sector in Manitoba
Bibliographic record
Abstract
This project surveyed social enterprises in Manitoba during the spring and summer of 2011 to \ndevelop clear indicators of their size, market activities, and socio‐economic contributions. In \nthis study, a social enterprise is defined as a business venture, owned or operated by a nonprofit \norganization that sells goods or provides services in the market to create a blended \nreturn on investment; financial, social, environmental, and cultural. Using this definition, \nresearchers identified 266 operating social enterprises in Manitoba. Of the 266 social \nenterprises that received the survey, 118 responded. Indicators of socio‐economic contribution \nincluded sales and revenue, expenditures, employment, volunteer engagement, and clients \nserved and trained. Respondents were asked to report results of the 2010 financial year. The \nfollowing report is a summary of the survey findings. \nPrior to revealing the survey findings, this paper provides a brief history of the innovative \napproaches to community economic development that have been used in Manitoba. The \nprovince’s roots in community‐based economic models laid the foundation for Manitoba’s \ncurrent social enterprises, which are found to be a diverse sector, composed of businesses \nmeeting a range of poverty reduction, social, cultural or environmental goals. The survey results \nsuggest that in 2010, the 118 responding social enterprises generated at least $55.4 million in \ncumulative revenue, including at least $41.5 million generated through sales. Responding social \nenterprises paid at least $25.3 million in salaries and wages to 3,752 people, of whom 3,450 were \nemployed as part of the mission of the organization. We estimate that Manitoba social enterprises \npaid, on average, just over $20,000 in wages and salary per full‐time equivalent employee. \nAdditionally, social enterprises trained 6,890 individuals, generated 5,870 volunteer \nopportunities, and provided services to an average of 4,200 people. This paper builds a strong case for stakeholders, community, funder, and government, to collaboratively value these distinct contributions and to support hospitable environments for social enterprises.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".