MATURE SOCIAL ECONOMY ENTERPRISE AND SOCIAL INNOVATION: THE CASE OF THE DESJARDINS ENVIRONMENTAL FUND
Bibliographic record
Abstract
ABSTRACT This study seeks to understand the nature and process of social innovation driven by mature social economy enterprises, and the innovative capability that supports it. The research examines enterprise capabilities by means of the institutional approach to social innovation and the Resource‐Based View theory (RBV). Based on grounded theory, this research focuses on a single case, the creation of the Desjardins Environment Fund (DEF). Launched 25 years ago,1DEF is the first mutual fund in North America to include extra‐financial criteria in its evaluation of business environmental management practices (fund securities) for the information of individual investors. The findings of this empirical research show how a major cooperative bank can generate social innovation and how this entails organizational innovations. The findings also reveal how these innovations benefit from the strategic and process resources that the Desjardins Movement managed to develop while taking into account both its core business (as a bank) and its purpose (as a cooperative). This study shows that the innovative potential of the mature social economy enterprise should not be underestimated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".