Strategies to Increase Membership in a Canadian Nonprofit Protecting Rights and Benefits of Retired Military Personnel
Bibliographic record
Abstract
Nonprofit organization leaders with an advocacy mission are increasingly challenged to identify, convert, and maintain their membership base to sustain the effectiveness of their advocacy reach and effectiveness. Grounded in stakeholder theory, the purpose of this qualitative single case study was to explore strategies some nonprofit leaders used to increase membership in a Canadian nonprofit protecting the rights and benefits of retired military personnel. The participants included four leaders of a small nonprofit organization in Ontario, Canada, who have directly or indirectly implemented membership strategies. Data were collected through semistructured interviews, client organizational documents, the organization’s website, an assessment of the client organization using the Baldrige Excellence Framework, and public information. The data were analyzed using thematic analysis, which yielded four themes: marketing reach, membership value proposition, nonprofit strategy and mission, and board governance. A key recommendation is for nonprofit organization leaders to define a new veteran-focused strategy and mission that meets the needs of its current stakeholders. Implications for positive social change include the potential to provide membership recruitment and retention strategies supporting the needs of veterans and their communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".