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Record W2064383120 · doi:10.5195/aa.2013.10

Active Aging: Hiking, Health, and Healing

2013· article· en· W2064383120 on OpenAlexaff
Rodney Steadman, Candace I. J. Nykiforuk, Helen Vallianatos

Bibliographic record

VenueAnthropology & Aging · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSocializationEmbodied cognitionContext (archaeology)EthnographyPerceptionPsychologyGerontologySocial psychologyMedicineSociologyGeography

Abstract

fetched live from OpenAlex

This article examines the illness and recovery experiences and perceptions of physically active middle aged and older adults participating in hiking groups. These perceptions are examined within the local milieu of their group and the larger social context of biomedical norms of healthy older bodies. Discourse on the body was viewed through the lens of medical anthropology and data were analyzed using embodied ethnography. There were 15 participants (53 percent female) and all were of European descent. The hiking group provided participants with meaningful spaces and places where they could explore all aspects of their health with the support of others who had undergone similar life experiences. The physical activities they engaged in as a group were therapeutic and transformational for several members. Their group activities created a deep sense of community and aided in their healing processes. Holistic health programs such as hiking groups could provide an alternative or ancillary treatment options. However, cost, location, opportunities for socialization, and the physical abilities of potential participants should be seriously considered before adopting a hiking program for this demographic.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.008
Scholarly communication0.0030.003
Open science0.0000.004
Research integrity0.0010.001
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 head0.038
GPT teacher head0.323
Teacher spread0.285 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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