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Record W2138895612 · doi:10.1123/jpah.2012-0115

Durations and Domains of Daily Aerobic Activity: Evidence From the 2010 Canadian Time-Use Survey

2014· article· en· W2138895612 on OpenAlexaffabout
Hugh Millward, Jamie Spinney, Darren M. Scott

Bibliographic record

VenueJournal of Physical Activity and Health · 2014
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsTime-use surveyPhysical activityAerobic exercisePsychologyGerontologyMedicinePhysical therapyChemistry

Abstract

fetched live from OpenAlex

BACKGROUND: This study employs national time-diary data to evaluate how much aerobic activity Canadians engage in on a daily basis, how that activity is apportioned by activity domain, and how subgroups within the population vary in their aerobic attainment. METHODS: The study employs time-use data from the 2010 General Social Survey of Canada, for 15,390 respondents aged 15 and older. To estimate effort levels, the authors harmonized survey codes with those in the Compendium of Physical Activities. Aerobic activity was defined as moderate or vigorous effort at 3.5 Metabolic Equivalent of Task (MET) or higher. RESULTS: Among the 4 activity domains, aerobic participation is highest in leisure activities, followed by chores, paid work, and active transportation (AT). Only a minority (42%) of respondents recorded at least 20 mins/day of aerobic activity. Aerobic totals were particularly low for women and those in poor or fair health, and low for students, 15- to 24-year-olds, and those residing in Quebec, Ontario, and larger cities. CONCLUSIONS: The majority of Canadian adults are failing to meet recommended aerobic activity levels. However, there is considerable opportunity to increase aerobic participation for some groups, particularly women and young adults, especially in the leisure and AT domains.

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)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.012
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.353
Teacher spread0.255 · 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 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

Citations12
Published2014
Admission routes2
Has abstractyes

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