Resource-Based View (RBV) of Unincorporated Social Economy Organizations
Bibliographic record
Abstract
ABSTRACT This article examines three related questions about unincorporated social economy organizations (USEOs): What are the characteristics of these social economy organizations? What is the unique bundle of resources that gives rise to and sustains their operations? Is there evidence of bricolage in these organizations? The findings suggest that USEOs are driven foremost by a social mission. USEOs provide diverse services and products including economic and specialized social activities, which are integral to the social fabric of society. The results also show that they combine and leverage two core resources – social capital and human capital – to support the operations of their organizations. Moreover they appear to draw on whatever resources are at their disposal to support the activities of the organization. This suggests that USEOs are involved in bricolage activities, which could explain the longevity of many of the organizations. RÉSUMÉ Cet article répond à trois questions étroitement liées sur les organismes d’économie sociale non constitués en société : Quelles sont les caractéristiques de ces organismes? Quelles sont les ressources particulières qui leur permettent de fonctionner? Ces organismes ont-ils recours au bricolage (dans le sens que Claude Lévi-Strauss prête à ce mot)? Les résultats indiquent qu’une mission sociale est ce qui motive les organismes d’économie sociale non enregistrés. Ces derniers fournissent une diversité de produits et services, y compris des activités économiques et sociales spécialisées qui sont essentielles pour la solidarité sociale. Les résultats montrent aussi que ces organismes combinent deux ressources clés – le capital social et le capital humain – afin d’appuyer le bon fonctionnement de leurs organisations. En outre, pour ce faire, ils ont apparemment recours à toute ressource qui soit à leur portée. Cette dernière pratique indique que les organismes d’économie sociale non constitués en société mènent vraisemblablement des activités de bricolage, ce qui pourrait expliquer pourquoi bon nombre de leurs organisations ont si longue vie.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".