Towards a community centred approach to corporate community involvement in the sporting events agenda
Bibliographic record
Abstract
Abstract The purpose of this paper was to examine ways that corporations can make a greater contribution to civic and community development through strategic ties to a city's development agenda surrounding the hosting of sporting events. Using the perspective of Corporate Community Involvement (CCI), we draw upon data collected as part of a larger study on sporting events and community development to explore how cities and corporations can make socially responsible contributions to communities. The guiding principles of community involvement in decision-making, full public disclosure and transparency, and grassroots legacy planning underscore the importance of community-based strategies for CCI. We offer three related strategies: comprehensive social and community impact assessments, facilitation of local knowledge capital and providers, and cross-sectoral management event programming as ways for corporations to begin to engage in CCI activities related to events. These strategies offer opportunities for organisation to use sport to make a valuable contribution to communities and community development activities.
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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 | 0.038 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.013 | 0.032 |
| Scholarly communication | 0.024 | 0.012 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".