FIFA's<i>Football for Health</i>: applying Kotter's eight-step programme for transformational change to a mass participation activity
Bibliographic record
Abstract
There was a time when ‘football medicine’ illustrated the grammar term ‘oxymoron’. Like the words ‘military intelligence’, football and medicine did not fit well together—the two provided anchors for a very wide spectrum. Why has that changed so that a scientific journal's cover shows a young boy whose eyes reflect hope, and a healthy future, largely because he is part of a football community? To address this question, and to challenge all sports federations to review their own efforts, we looked to Harvard leadership professor, John P Kotter.1 His eight principles for strategic change resonate in diverse settings, including publicly traded companies and non-profit businesses. We discuss their relevance to Federation Internationale de Football Association (FIFA) and its Football for Health programme to highlight a model that other global sporting organisations and national federations could adopt. Please also see the BJSM blog where you can link to a related podcast (http://blogs.bmj.com/bjsm/). Kotter argues that urgency is critical. This is not easy—the dearth of ‘sport for health’ programmes across national sporting federations and international organisations underscores his point. Success requires ‘change champions’, and to this extent FIFA President Sepp Blatter deserves tremendous credit. Blatter's leadership has been remarkable for moving health from irrelevance to pre-eminence in a major sport.2 Blatter and the Chair of the FIFA Medical Assessment and Research Centre (F-MARC), Professor Jiri Dvorak, supported by Dr Michel D'Hooghe, Chair of FIFA Medical Committee, convened national sporting organisation leaders together with a sports medicine lead from almost 200 countries to the first Football for Health conference (Zurich, 2009). That is how FIFA/F-MARC conveyed a sense of urgency. The meeting was not a talk-fest, but carefully structured to obtain buy-in for the concept of having active ‘medical commissions’ in each country. One goal for FIFA. Kotter tells us …
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".