MétaCan
Menu
Back to cohort

Do Public Health and Social Participation Matter for the Elderly? An Analysis of an Aging Community in Khuzistan Province, Iran

2011· article· en· W1572298241 on OpenAlexvenueno aff
Abdolrahim Asadollahi, Laleh Fani Saberi, Alireza Mohseni Tabrizi, Nasrin Faraji

Bibliographic record

VenueCanadian social science · 2011
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAlienationWelfarePopulationScale (ratio)LiteracyPsychologyEconomic growthGerontologySocioeconomicsSociologyPolitical scienceGeographyDemographyMedicine

Abstract

fetched live from OpenAlex

Increasing aged population (3.1%) compared with natural growth of Iranian population (1.2%) is a problematic issue. The literatures acclaim that physical disabilities and health problems in end life have significant relationship with social participation of aged. This study illustrates social participation in Iranian background, its factors and obstacles especially among aged. The scale of aged participation (SAP) constructed according to selected theories in 4 basic items and its 35 sub items. The community of the study is aged people in four selected cities of Khuzistan province/Iran: Ahwaz, Behbahan, Mah-Shahr, Dezful, and Abadan in 2010, and sampled 768 urban and rural elders. Findings have mentioned that social participation is low. It has significant relationship with burgess, high literacy, ethnicity, living with children, feminine, growth of welfare, having chronic disease of respiratory disorder, social alienation, cost of participation, reduction in benefits of participation, growth of their child’s income. Key words : Elderly; Social Participation; Literatures; Obstacles; Factors; Khuzistan Cities (Iran)

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.138
GPT teacher head0.408
Teacher spread0.270 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueCanadian social scienceSame topicHealth and Well-being StudiesFrench-language works237,207