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Record W2019639169 · doi:10.1353/cja.2004.0022

Social Isolation and Loneliness: Differences between Older Rural and Urban Manitobans

2004· article· en· W2019639169 on OpenAlex
Betty Havens, Madelyn Hall, Gina Sylvestre, Tyler Jivan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsLonelinessSocial isolationPsychologyGerontologySample (material)DemographyIndex (typography)Isolation (microbiology)MedicineSocial psychologySociologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

The purpose of this paper was to identify predictors of social isolation and loneliness for very old rural and urban adults. With data from the 1996 Aging in Manitoba Study (N = 1,868; age range 72-104), separate multiple regression models were constructed for rural and urban sub-samples, using the life space index (LSI) to measure social isolation as one outcome, and a loneliness index created by the authors from a combination of items to measure loneliness as a second outcome. Different factors were found to predict the outcomes for the two sub-samples. The models with isolation as the outcome produced five predictors for the rural sub-sample and three for the urban sub-sample. Only living alone was the same for both groups. The models with loneliness as the outcome produced five predictors for the rural sub-sample and two for the urban sub-sample, again with only one factor in common--four or more chronic illnesses. We conclude that health and social factors are important predictors of social isolation and loneliness, and sensitivity to these factors may improve the experience of older adults.

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.

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)0.001
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 score0.589
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.020
GPT teacher head0.264
Teacher spread0.244 · 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