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Record W4313477886 · doi:10.1080/15350770.2022.2161688

Rooming with Seniors: Investigating Demand for Intergenerational Home-Sharing Arrangements Amongst Students at a Canadian University

2023· article· en· W4313477886 on OpenAlexaffabout
Carling Fraser, Patricia Collins

Bibliographic record

VenueJournal of Intergenerational Relationships · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsRentingLonelinessSharing economyPsychologyBusinessSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Intergenerational home-sharing programs are often touted as solutions for reducing loneliness amongst seniors and rental costs for post-secondary students. Yet, little is known about the demand for such living arrangements. This study investigated the receptivity of post-secondary students to intergenerational home-sharing in a Canadian city through an online survey of over 3,800 university students in March 2019. Only 15% of respondents expressed interest in home-sharing, and experience volunteering with older adults was the strongest predictor of interest. These findings offer important insights for cities across Canada that are exploring the feasibility of student-senior home sharing programs in their own jurisdictions.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.296
Teacher spread0.245 · 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 designQualitative
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
Published2023
Admission routes2
Has abstractyes

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