A Framework of Strategic Approaches to Membership Growth in Nonprofit Community Sport
Bibliographic record
Abstract
Engaging in strategic planning may help leaders of community sport organizations (CSOs) to develop strategic thinking as well as build capacity to sustain and expand their programs despite environmental uncertainty. This study proposes a framework for understanding how the membership growth strategies of CSOs are shaped based on their environment. Semi-structured interviews with presidents of CSOs, alongside analysis of strategic plan documents, were used to identify strategic imperatives that CSO leaders 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 approaches: Trailblazers, Enhancers, Maintainers, and Carers. Each approach is described in detail and implications for strategic management in community sport 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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".