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Record W4405977242 · doi:10.1093/geroni/igae098.1106

WHO FITS AND HOW? SUPPORTING TENANCY AND FOSTERING BELONGING IN HOUSING FOR OLDER PERSONS EXPERIENCING HOMELESSNESS

2024· article· en· W4405977242 on OpenAlexaboutno aff
Lena Rebecca Richardson, Rachel Weldrick, Tam Perry

Bibliographic record

VenueInnovation in Aging · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsLeasehold estateGerontologyMultitenancyPsychologyPolitical scienceMedicineComputer scienceOperating system

Abstract

fetched live from OpenAlex

Abstract Homelessness among adults age 50+ years is increasing across North America. The Aging in the Right Place (AIRP) Partnership is a 5-year study of eleven promising practice organizations addressing older adult homelessness in three Canadian cities. This symposium will share findings from AIRP research on what supports a sense of belonging and social integration among older persons experiencing homelessness (OPEH) within temporary and permanent supportive housing programs. Presenters include interdisciplinary researchers with a diversity of perspectives stemming from gerontology, education, and social work. The symposium will begin with Erisman presenting a study of service providers’ perspectives on who is eligible for services and what actions providers can undertake to support clients’ ongoing tenancy in shelter/housing organizations. Weldrick will then discuss mechanisms for successfully supporting social integration from a study with OPEH in a temporary housing program. Following, Richardson will present findings on how multidirectional caring relations can foster belonging in a homeless shelter for older adults fleeing abuse. Finally, Walsh’s study findings will highlight ways to promote AIRP for male veterans in a temporary housing program. Tam Perry, an expert in housing transitions for older adults, will discuss the implications of these papers and reflect on processes of social integration and cultivating belonging for OPEH in temporary and permanent housing. Together, participants of the symposium will advance this emerging scholarship using a wide range of methods and perspectives.

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)0.006
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.009
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0020.003
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 head0.062
GPT teacher head0.414
Teacher spread0.352 · 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
Published2024
Admission routes1
Has abstractyes

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