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Record W2884625888 · doi:10.1017/s0144686x18000788

‘I don't want to be, feel old’: older Canadian men's perceptions and experiences of physical activity

2018· article· en· W2884625888 on OpenAlexaffabout
Laura Hurd Clarke, Lauren Currie, Erica Bennett

Bibliographic record

VenueAgeing and Society · 2018
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPleasurePerceptionPsychologyGerontologyPhysical activityPsychological interventionExtant taxonQualitative researchSocial psychologySociologyMedicinePhysical therapyPsychotherapist

Abstract

fetched live from OpenAlex

Abstract Relatively few older adults are physically active despite extensive research exploring barriers and facilitators and concomitant interventions designed to enhance participation rates. Building on the growing literature that considers the subjective experience of being physically active, we explored the meanings that older Canadian men attributed to physical activity broadly defined. Thus, we examined their experiences and perceptions of exercise, sport and/or leisure-time physical activities. Data are presented from qualitative interviews with 22 community-dwelling Canadian men aged 67–90. Our analysis resulted in three overarching categories that subsumed the men's understanding of physical activity. ‘I do it for my health’ described how the men stated that their primary reason for engaging in exercise was to maintain their health and body functionality so that they could age well and continue to participate in sport and leisure. ‘It feels good’ referred to the various ways that the men derived pleasure from being active, including the physical sensations, psychological benefits and social connections they derived from their participation. ‘It gets tougher’ detailed the ways that the men were finding physical activity to be increasingly difficult as a result of the onset of health problems, declining body functionality and the social realities of ageing. We discuss our findings in light of the extant literature concerning age relations, ageism, and the third and fourth ages.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0140.006
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.319
Teacher spread0.293 · 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 designQualitative
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

Citations22
Published2018
Admission routes2
Has abstractyes

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