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Record W3208311699 · doi:10.1093/geront/gnab155

Perceptions of Risk: Perspectives on Crime and Safety in Public Housing for Older Adults

2021· article· en· W3208311699 on OpenAlexafffund
Christine Sheppard, Sarah Gould, Andrea Austen, Sander L. Hitzig

Bibliographic record

VenueThe Gerontologist · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsFeelingFocus groupAccountabilityService providerQualitative researchPublic relationsBusinessAging in placeWork (physics)Risk perceptionPerceptionService (business)PsychologyMarketingSocial psychologyEngineeringGerontologyMedicineSociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: An increasing number of older adults are aging in place in public housing. Public housing is perceived to have higher rates of crime that have detrimental impacts on health and well-being. We used a qualitative approach to understand the experiences of safety and unsafety for older adults in public housing. RESEARCH DESIGN AND METHODS: Participants included older adult tenants (n = 58) as well as service providers (n = 58) who offer supports directly in the buildings. Semistructured qualitative interviews and focus groups were used to explore (a) what makes the buildings feel unsafe, (b) how safety concerns affect access to support services, and (c) strategies used to promote safety. RESULTS: Participants acknowledged the importance of safety for creating a home-like environment; however, many described feeling unsafe at home or work. Participants described extreme examples of antisocial behaviors that were pervasive and viewed as commonplace. Lack of building security was a key issue, which was compounded by a perceived lack of accountability. While service providers were willing to accept a certain level of risk, many acknowledged that unsafe situations forced them to withdraw in-home services or stop community programs, further contributing to feelings of unsafety. In the absence of effective formal security, participants described several measures taken to mitigate risk. DISCUSSION AND IMPLICATIONS: Our findings point to the need for enhanced physical and environmental safety infrastructure, improved building management, increased on-site security, as well as other proactive measures to reduce risk by creating a greater sense of connection and community within the buildings.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.494
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.038
GPT teacher head0.330
Teacher spread0.292 · 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 teacher head, 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

Citations15
Published2021
Admission routes2
Has abstractyes

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