Nonprofits and the Promotion of Civic Engagement: A Conceptual Framework for Understanding the "Civic Footprint" of Nonprofits within Local Communities
Bibliographic record
Abstract
ABSTRACT The literature suggests that nonprofit organizations provide civic benefits by promoting engagement within local communities. However, there exists minimal empirical evidence describing the ways in which nonprofits actually undertake this role. In order to address this omission, we conducted interviews with personnel of nonprofit organizations in one rural community in the United States. Our preliminary findings indicate that nonprofit organizations promote civic engagement through programs and activities that: 1) engage volunteers and donors; 2) bring community members together; 3) collaborate with organizations within and beyond the community; and 4) promote community education and awareness. Together, these findings help to develop a working model to understand the civic footprint of nonprofit organizations with methodological implications for future research that would seek to measure the extent to which nonprofits promote civic engagement. Il est normal de supposer que les associations à but non lucratif favorisent l’engagement du citoyen dans les communautés locales. Cependant, il existe peu de données empiriques sur la manière dont ces associations assument véritablement ce rôle. Pour combler ce manque, nous avons mené des entretiens semi-directifs approfondis auprès du personnel d’associations à but non lucratif dans une petite communauté rurale aux États-Unis. Nos résultats préliminaires indiquent que ces associations motivent les citoyens à s’impliquer quand elles offrent des programmes et des activités qui : 1) intéressent les bénévoles et les donateurs; 2) rassemblent directement ou indirectement les membres de la communauté; 3) collaborent avec d’autres associations tant au sein de la communauté qu’au-delà de celle-ci; et 4) encouragent l’éducation et la conscientisation communautaires. Ces constats aident à établir un modèle pour mieux comprendre la présence civique des associations à but non lucratif dans les communautés et indiquent une piste à suivre pour des recherches futures qui examineraient l’influence de ces associations sur le niveau de participation civique.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".