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Record W3198616015 · doi:10.4324/9781003159063-9

Coaching Older Adults (Aged 55+)

2021· book-chapter· en· W3198616015 on OpenAlexaffabout
Rylee A. Dionigi, Rochelle Eime, Bradley W. Young, Bettina Callary, Scott Rathwell

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldPsychology
TopicCoaching Methods and Impact
Canadian institutionsUniversity of LethbridgeCape Breton UniversityUniversity of Ottawa
Fundersnot available
KeywordsCoachingPsychologyMedicineGerontology

Abstract

fetched live from OpenAlex

Despite the benefits community sport can bring to older adults (aged 55+), such as social support, mental, and physical health and fun, national sporting policies tend to focus on young age groups in terms of participation and elite performance, so community sports are often required to align their strategic focus with these policies. Therefore, there are scant (yet emerging) sporting policies, formal sport coaching, and coach education opportunities specific to older adults in countries such as Australia, New Zealand, England, and Canada. This reality poses problems for coaching older adults in community sports. However, there is recent research, particularly in Canada, that reveals the everyday realities of coaching older adults, such as the importance of meeting athlete needs for competition, health and/or fun, developing personal relationships, accounting for age-related changes, and applying adult learning principles to the coaching context. In this chapter, we discuss these factors and offer some strategies to assist those embarking on community sport coaching work with older adults.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.012

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 head0.043
GPT teacher head0.348
Teacher spread0.305 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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 routes2
Has abstractyes

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