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Record W4399772197 · doi:10.36315/2024inpact022

Quality of life in aging: A survey for co-living

2024· book-chapter· en· W4399772197 on OpenAlexfundaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsQuality of life (healthcare)GerontologyPsychologyMedicine

Abstract

fetched live from OpenAlex

Aging populations are faced with increasing challenges.The idea is to live well and be serene throughout retirement.Financial constraints add to the burden in today's society.Post-COVID additional stresses have been identified.In our study we aimed at uncovering characteristics for the creation of a survey to identify seniors with suitable characteristics for co-living arrangements.In this research we look at retired independent women living in the government subsidized rental co-living building in Paris in order to establish desirable criteria to adopt or adapt the formula in Canada.At present there are no such arrangements that have lasted, despite some examples of friends living together.As well, retirement homes are costly and often do not meet the needs of more independent people.Living alone in aging has also become fraught with issues.Studies have shown that people living together while also keeping independent enjoy longer healthier lives.For this qualitative study, the first step was to have members of a successful co-living model make regular journal entries for six months so as to identify desirable traits and attitudes through their ways of being and doing.The journals were analyzed along with data found in the public domain on the group, including the House Charter each member had to sign and abide by.Identified categories were grouped into themes.Following that we searched established well-being surveys to tease out corresponding questions to the items we had uncovered.We then created a questionnaire with a 5-point Likert.This questionnaire is presented under a format with radio buttons.The final questionnaire includes 33 theme sections with various numbers of questions under each section going from one to 17 for autonomy.The autonomy section as the most important one is further subdivided into four sections.The themes will be explored and discussed in light of our findings and their relevance.Further steps will be presented as well as suggestions for further research.

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)0.005
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 score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.219
GPT teacher head0.488
Teacher spread0.269 · 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
Published2024
Admission routes2
Has abstractyes

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