Through on Goal: Soft Power, Sporting Sovereignty and the History of the Confederation of North, Central America and Caribbean Association Football (CONCACAF) Recognition of Non-Sovereign, Subnational Member Territories
Bibliographic record
Abstract
This article examines the history of the composition of member federations of the Confederation of North, Central America and Caribbean Association Football (CONCACAF) in men’s football. In particular, the recognition and admittance of several non-sovereign jurisdictions is reviewed. Utilizing the lenses of sporting sovereignty and soft power, this article discusses the acceptance of non-sovereign jurisdictions and the larger power dynamics between the North America, Central America and the Caribbean member unions. Further dynamics between the inconsistency of recognition and status of non-sovereign member territories of CONCACAF and broader FIFA affiliation and membership are also explored. This article highlights the impacts of these actions for CONCACAF as an institution and what this legacy means for contemporary impacts. The recent particular case of Greenland’s application to join CONCACAF in contrast to their unsuccessful efforts to join the Union of European Football Associations (UEFA) is employed as a comparative case in this regard. The rationale and factors put forward and driven by these non-sovereign territories represent the employment of paradiplomacy for broader jurisdictional aims.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".