MétaCan
Menu
Back to cohort
Record W4404082486 · doi:10.1080/19406940.2024.2424577

Sport for development in German development cooperation: early and unknown efforts

2024· article· en· W4404082486 on OpenAlexaboutno aff
Katrin Bauer, Louis Moustakas

Bibliographic record

VenueInternational Journal of Sport Policy and Politics · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsGermanPolitical sciencePublic administrationPublic relationsProcess managementBusinessHistory

Abstract

fetched live from OpenAlex

The early involvement some Western liberal states, such as Norway and Canada, in the field of Sport for Development (SfD) is well known, with both countries regarded amongst the pioneers in this area. In contrast, Germany’s early investments in the field are not widely known, in part due to deficiencies in documentation and publication. This paper will not only challenge the deficient historical documentation on the subject but will also provide a preliminary descriptive account of the factors that have driven investment or withdrawal from the SfD sector within Germany. This will be set against a broader global context and in relation to key turning points affecting the field. Based on a literature review and content analysis, the results trace the chronological course and development of SfD in Germany in three phases, where the popularity of sport as a developmental tool is subject to strong fluctuations. Additionally, German efforts in SfD have differed from international trends, particularly in the early adoption of sport in German development cooperation in the mid-1970s and the constraints observed during SfD’s international growth in the 2000s. Key implications of this paper include highlighting the strong influence of domestic politics on SfD funding and activity, and formally documenting the breadth and scale of German SfD efforts. Overall, this paper provides a foundation for further work looking at German international SfD efforts, as well as future consideration of the role of national politics in SfD funding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.380
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Theoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Sport Policy and PoliticsSame topicSport and Mega-Event ImpactsFrench-language works237,207