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Record W3128453443 · doi:10.22158/grhe.v4n1p48

International Perspectives of Strategic Team and Player Development in Diverse Amateur/Grassroots 60+ Small-Sided Football Contexts

2021· article· en· W3128453443 on OpenAlexaff
Harry Hubball, Jorge Díaz-Cidoncha García

Bibliographic record

VenueGlobal Research in Higher Education · 2021
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGrassrootsAmateurFootballCoachingPublic relationsPolitical scienceBusinessManagementEconomics

Abstract

fetched live from OpenAlex

Despite the significant growth of amateur/grassroots over-60s (60+) small-sided football in diverse indoor and outdoor settings around the world, scant attention has been afforded to related research, coach education, and strategic team and player development initiatives within these unique seniors‘ football contexts. Drawing upon case study methodology using multiple-case design, this paper examines whether and how Strategic Team and Player Development (STPD) initiatives are implemented in diverse amateur/grassroots 60+ small-sided football coaching contexts. Data suggest there is substantial interest among players and coaches for age-appropriate STPD initiatives, which require organization-specific support structures and integrated, progressive, and evidence-based activities customised for the unique needs and competitive circumstances of players/participants. STPD initiatives can significantly enrich participant experiences and maximize program outcomes such as player and team skills and sustained participation. STPD initiatives in these contexts are still in the early stages, both theoretically and practically. While there are many challenges and areas for improvement, strategic organizational support including a commitment to customised football coach education can be the basis for implementing STPD in diverse amateur/grassroots 60+ small-sided football contexts. Key challenges and implications for customised football coach education are discussed.

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

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.210
GPT teacher head0.468
Teacher spread0.258 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
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

Citations0
Published2021
Admission routes1
Has abstractyes

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