Employer supported volunteering programs in large corporations
Bibliographic record
Abstract
The term Social Economy has been used for years to describe a segment of the economy that is neither driven by the profit motives of private interests, nor owned by the state to serve public interests. Often referred to as the third sector, (distinct from the private for-profit sector and public sector) it defies clear boundaries (Moulaert & Ailenei, 2005). Thus definitions of the social economy vary. In the US the term social economy is not used at all; there the third sector refers strictly to organizations that adhere to the non-distribution-of-profits rule stipulated by the US Internal Revenue System (Graefe, 2006). In Quebec, the term Social Economy has been in use for several decades, but refers to a partnership between state and third sector organizations and an exercise in stemming the tide of neo-liberal globalization (Graefe, 2001). In Ontario and the rest of Canada, reference to a Social Economy is more recent and the concept is applied in a broader manner, in keeping with some European notions of the Social Economy (Fonatan & Shragge, 1997). This broader conceptualization eschews strict adherence to non-distribution stipulations and includes cooperatives and social enterprises in addition to nonprofit organizations. Keywords: CVSS, Centre for Voluntary Sector Studies, Working Paper Series,TRSM, Ted Rogers School of Management Citation:
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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".