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Record W2125530118 · doi:10.1177/0733464807300224

Older Persons Relocating With a Family Caregiver

2007· article· en· W2125530118 on OpenAlexaffabout
Oscar E. Firbank, Janique Johnson‐Lafleur

Bibliographic record

VenueJournal of Applied Gerontology · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsRelocationCohabitationResidenceDiversity (politics)Variety (cybernetics)PsychologySample (material)GerontologyDuration (music)DemographySociologySocial psychologyMedicineGeography

Abstract

fetched live from OpenAlex

In North America, a significant number of families who care for an elderly relative relocate in the same residence. However, research has paid little attention to the process that precedes such relocation. This article aims at studying this process by examining the experiences of a sample of Canadian elderly and their caregivers, born in Quebec and in Haiti. The article highlights that in spite of diversity, moving in together usually occurs in stages and follows a relatively lengthy process in which transitory living arrangements are not uncommon. In addition, a range of events, hospital stays in particular, act as markers between stages or shorten their duration. It appears that cohabitation trajectories differ according to origin and generational group. Noteworthy is that home-care services did not greatly influence the cohabitation decision of respondents from either group. Most respondents claim that the decision to relocate together was consensual but motivated by a variety of reasons.

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)0.002
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 score0.146
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.296
Teacher spread0.275 · 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

Citations15
Published2007
Admission routes2
Has abstractyes

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