Social return on investment at Inspirations Studio
Bibliographic record
Abstract
Inspirations Studio is a “micro-business incubator for low income women who have been impacted by poverty, homelessness, trauma and mental health issues (About Us, n.d).” The Toronto nonprofit social enterprise helps its members ‘learn pottery and business skills so that they can earn income’ (About Us, n.d). The women members are self-employed, operating independent micro-businesses; at the studio they learn to make pottery and to run a business, sell the pottery they make, and use the income from the sales to better their lives. Although the women retain most of the earnings from the sale of their Inpirations-made pottery, they also pay the studio a fee for use of its facilities and clay materials. Because it is business with a social purpose – to teach disadvantaged women to make and sell pottery and by so doing, enhance their well-being, and commercial - to create and sell quality products – it is considered to be a social enterprise. A recent case study of the organization found that, for a relatively low budget operation, Inspirations Studio generates enough benefits to its stakeholders to make it well worth the investment in the social enterprise (Meinhard, Lok & O’Connor, 2014). The case study used a systems-analytic, value-proposition framework to identify the elements and relationships necessary to create and deliver value to the stakeholders of the organization. Keywords: CVSS, Centre for Voluntary Sector Studies, Working Paper Series, TRSM, Ted Rogers School of Management
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.119 | 0.016 |
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".