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Record W3081839096 · doi:10.36713/epra4983

COMPARISON OF SELECTED DOMAINS OF QUALITY LIFESTYLE BETWEEN INDIANS AND INDIAN CANADIANS

2020· article· en· W3081839096 on OpenAlexaffabout
Jaideep S. Bains, Sagarika Bandyopadhyay, Arup Gayen

Bibliographic record

VenueEPRA International Journal of Research & Development (IJRD) · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPerspective (graphical)Sleep hygieneQuality of life (healthcare)Healthy eatingGerontologyHygienePhysical healthPsychologyPhysical activityMental healthSleep qualityMedicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

The quality of various domains in life leads to life satisfaction which is essential for a balanced existence. From the perspective of physical and mental health, family, education, employment, wealth, safety & security to freedom, religious beliefs and the environment –all entities of a human life are involved to it. Attempt has been made to consider three major aspects of a quality life namely, mindful eating, physical activity and sleep hygiene to denote the status of behavioural habits of people living in India and Canada. 373 subjects, 234 from India and 139 from Canada, were selected conveniently for this study. It is observed that Canadian community is significantly superior in habits of mindful eating and physical activities in comparison to Indian subjects. However, no significant difference was found in sleep hygiene between the subjects living in India and Canada. KEY WORDS: Mindful eating, Physical Activity, Sleep Hygiene

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.449

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.135
GPT teacher head0.487
Teacher spread0.352 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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