Developing a multi-level framework for analyzing public sports-based programmes to integrate migrants and refugees into organized sports
Bibliographic record
Abstract
Voluntary sports clubs (VSCs) are viewed by governments as an important catalyst for the integration of migrants/refugees. However, research has shown that only a small number of VSCs are directly involved in ‘integration through sport’ practices. To increase the number of VSCs that are willing and able to significantly implement targeted integration measures, it is necessary to understand how ‘integration through sport policies’ can actually reach the local level and impact practices. In this paper, we propose a conceptual framework that considers and bundles current integration research in organized sports. To address the complexity, a multi-level framework will be developed that helps to understand the roll-out strategies and implementation processes of integration programmes for migrants in organized sports. Additionally, it helps to support practitioners in developing appropriate evaluation schemes, or revising existing integration programmes at the local, regional or national level in order to increase the number of integrative VSCs.
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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 | 0.016 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".