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Record W2945509288

Health, fitness, and life satisfaction in retired teachers

2017· dissertation· en· W2945509288 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typedissertation
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsLife satisfactionPsychologyGerontologyMedicineMedical educationSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to describe the health, fitness, and life satisfaction of retired
\nteachers in Thunder Bay. Forty retired teachers (24 women, 16 men) aged 55 to 70 years
\nparticipated in the study. Fitness level, physical activity participation, and lifestyle habits
\nwere measured according to the protocol of The Canadian Physical Activity, Fitness, and
\nLifestyle Appraisal (CPAFLA), and compared to Estimated Health Benefit Zones. Fitness
\nlevel was also compared to norms from the 1981 Canada Fitness Survey (CFS). Over
\n50% of the sample scored Good or higher on all fitness measures, and on measures of
\nphysical activity participation and lifestyle habits, over 90% scored in this range.
\nComparisons to the CFS revealed average fitness levels, not markedly different from the
\ngeneral Canadian population. Levels of high density lipoproteins (HDL), low density
\nlipoproteins (LDL), and triglycerides, as well as the ratio of total cholesterol to HDL were
\nin a range designated as healthy or desirable for at least 50% of the sample. Self-report
\nmeasures indicated a high level of satisfaction with retirement life, and extremely healthy
\nlifestyle behaviours. Both perceived health and life satisfaction were significantly
\ncorrelated with aerobic fitness, indicating possible benefits of maintaining a physically
\nactive lifestyle during retirement. Retired teachers were found to be in good physical
\nhealth, possess exceptionally healthy behaviours with respect to lifestyle and physical
\nactivity participation, and be extremely satisfied with retirement life.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.320
Teacher spread0.269 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

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