A Leisure Professional Association Creating an Action Plan for Change: Part 2
Bibliographic record
Abstract
Abstract In 2016 North Carolina Recreation and Parks Association (NCRPA), a leisure and recreation professional association, implemented an organizational change with the hopes of becoming more relevant and vital to recreation professionals. James and Weddell documented the initial process leading to organizational change. The NCRPA Board president tasked an Ad Hoc committee to read the book, “Race for Relevance” (2011) and make recommendations to revitalize the organization. For more details on the beginning process, see James and Weddell’s case study “A Leisure Professional Association’s Structural Change, to Remain Relevant to its Members as well as in its Support of the Profession – Part 1”. Organizational change includes more than making recommendations to a board and having a unanimous board vote to implement the recommendations. Once the vote passed, the real work began. This case study continues the investigation by describing the implementation process of the recommendations leading to NCRPA organizational revitalization for 2017. The main players of innovation included the NCRPA Executive Director, its Board President, and the Executive Board as well as several committees appointed by the President. NCRPA continued to use the book “Race for Relevance” (2011) as a primer to change, requiring each committee member to read the book to understand the impact of the changes and future decisions. VIU logo WLCE logo Information Vancouver Island University World Leisure Centre of Excellence © Melissa Weddell and Jana Joy James 2018
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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 | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.034 | 0.007 |
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".