Towards a Framework of Strategic Approaches for Membership Growth in Nonprofit Community Sport
Bibliographic record
Abstract
Engaging in a strategic planning process may help nonprofit managers to develop strategic thinking as well as build capacity to sustain and expand their programs and services despite environmental uncertainty. This study proposes a typology for understanding how the membership growth strategies of community sport organizations, as one focal nonprofit context, are shaped based on their environment. Semi-structured interviews with fifteen presidents of nonprofit organizations, alongside analysis of strategic plan documents, were used to identify strategic imperatives that nonprofit managers considered when formulating their organizational strategies. These imperatives were grouped into two dimensions: organizational readiness for growth and environmental dynamism. These dimensions were then juxtaposed to create a matrix of four strategic types: Trailblazers, Enhancers, Maintainers, and Carers. Each type is described in detail and implications for practice are discussed.
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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 | 0.016 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.008 | 0.033 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".