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Record W2986395175 · doi:10.1093/geroni/igz038.786

GOALS OF THE ENDGAME

2019· article· en· W2986395175 on OpenAlexaff
Michelle Pannor Silver

Bibliographic record

VenueInnovation in Aging · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIdentity (music)PsychologyPerspective (graphical)AthletesLife course approachEliteNarrativePhysical bodyPersonal identitySocial psychologySelf-conceptPolitical scienceMedicineAestheticsPhysical therapy

Abstract

fetched live from OpenAlex

Abstract At all stages of life, the body can be considered an occupational resource that interacts with social structures in identity formation and complicates personal adaptation to life transitions. As the body declines, the economic and social standing it confers also tends to decline, leading to socially embedded fears about physical decline and marginalization. This paper applies theoretical work from embodiment theory and the life course perspective to examine how perceptions of aging and life experience with sport (or lack thereof) influence exercise participation and athletic identity. Using a narrative approach, I examine in-depth interviews I conducted with elite athletes, masters’ athletes, coaches, athletic program directors, mature adults. Some participants struggled to exercise regularly, and others are exercising more in their later years than at any other point in their lives. Three key themes emerged: 1) bodily identity is tremendously important in relation to other forms of identity when it is affected by aging, ill-health, or other physical processes; 2) physical functional mobility becomes increasingly important with age; and 3) experiences with sports and athletic identity (or lack thereof) influence engagement in exercise in later life in surprising ways. The paper challenges society’s focus on youth in sports and elite athletes, to discuss how our greater longevity means that we must place more emphasis on identifying ways to keep physically active and mobile throughout adulthood.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0050.002
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0840.033

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 head0.034
GPT teacher head0.324
Teacher spread0.289 · 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
GenreCommentary

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
Published2019
Admission routes1
Has abstractyes

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