MétaCan
Menu
Back to cohort
Record W2897707364 · doi:10.1093/geronb/gby126

Housing Transitions and Recovery of Older Adults Following Hurricane Sandy

2018· article· en· W2897707364 on OpenAlexfundno aff
Alexis A. Merdjanoff, Rachael Piltch‐Loeb, Sarah Friedman, David M. Abramson

Bibliographic record

VenueThe Journals of Gerontology Series B · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
FundersYork UniversityState of New Jersey Department of Health
KeywordsPsychologyEnvironmental science

Abstract

fetched live from OpenAlex

OBJECTIVES: This study explores the effects of social and environmental disruption on emergency housing transitions among older adults following Hurricane Sandy. It is based upon the Sandy Child and Family Health (S-CAFH) Study, an observational cohort of 1,000 randomly sampled New Jersey residents living in the nine counties most affected by Sandy. METHODS: This analysis examines the post-Sandy housing transitions and recovery of the young-old (55-64), mid-old (65-74), and old-old (75+) compared with younger adults (19-54). We consider length of displacement, number of places stayed after Sandy, the housing host (i.e., family only, friends only, or multi-host), and self-reported recovery. RESULTS: Among all age groups, the old-old (75+) reported the highest rates of housing damage and were more likely to stay in one place besides their home, as well as stay with family rather than by themselves after the storm. Despite this disruption, the old-old were most likely to have recovered from Hurricane Sandy. DISCUSSION: Findings suggest that the old-old were more resilient to Hurricane Sandy than younger age groups. Understanding the unique post-disaster housing needs of older adults can help identify critical points of intervention for their post-disaster recovery.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.310
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.320
Teacher spread0.294 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe Journals of Gerontology Series BSame topicDisaster Management and ResilienceFrench-language works237,207