Perceptions of Risk: Perspectives on Crime and Safety in Public Housing for Older Adults
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".