Pathways to Local Partnerships in a Semi-Rural Setting: A Qualitative Study of Community Engagement and Employer-Supported Volunteering in Small and Medium Enterprises and Local Nonprofits
Bibliographic record
Abstract
There remains a knowledge gap regarding the factors that drive the development of business-nonprofit partnerships in the context of employer-supported volunteering—especially in small and medium enterprises. Furthermore, there is a need to consider how enterprises operate in their cultural contexts to better understand how they support volunteering trends in Canada. This study aimed to improve understanding of the multi-level factors that foster the development of business-nonprofit partnerships in the context of employer-supported volunteering. Fifteen semi-structured interviews were conducted with community and small business actors in a semi-rural setting in Francophone Québec. Results challenged the traditional view of volunteer support as a distinct activity, showing an integrated system of inter-dependence. Results suggest the relevance of conceptualizing small enterprises’ support of volunteering as part of an inclusive approach to community engagement. RÉSUMÉLes facteurs liés au développement de partenariats entre entreprises et OBNL dans le contexte du bénévolat appuyé par l’employeur sont méconnus – particulièrement au sein des petites et moyennes entreprises. Il est également pertinent de considérer le contexte culturel pour mieux comprendre les tendances canadiennes du bénévolat appuyé par l’employeur. Cette étude vise l’obtention d’une meilleure compréhension des facteurs multiniveaux associés au développement de partenariats entreprises-OBNL dans le contexte du soutien au bénévolat. Quinze entretiens semistructurés ont été effectués auprès d’acteurs du secteur communautaire et des petites entreprises dans un milieu semi-rural francophone-québécois. Les résultats repositionnent la notion d’activités distinctes et témoignent plutôt d’un système intégré d’interdépendances. Les résultats suggèrent de conceptualiser le soutien au bénévolat des petites entreprises au sein d’une approche inclusive d’engagement communautaire.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".