MétaCan
Menu
Back to cohort
Record W2903217436 · doi:10.1111/disa.12299

A modified Community Assessment for Public Health Emergency Response (CASPER) four months after Hurricane Sandy

2018· article· en· W2903217436 on OpenAlexaboutno aff
Saleena Subaiya, Joshua Stillman, Yoanna S Pumpalova

Bibliographic record

VenueDisasters · 2018
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthEnvironmental healthSuicide preventionPoison controlOccupational safety and healthQuarter (Canadian coin)Medical prescriptionInjury preventionNeeds assessmentMedical emergencyDemographicsHuman factors and ergonomicsMedicineSocioeconomicsBusinessGeographyNursingPolitical scienceEconomicsDemographySociology

Abstract

fetched live from OpenAlex

This study sought to assess access to utilities, basic needs, financial burden, and perceived safety among households in the Rockaway Peninsula of New York City, United States, four months after Hurricane Sandy struck in 2012. A modified cluster survey design was used to select households for inclusion in the study. Survey content was created using the Community Assessment for Public Health Emergency Response (CASPER) toolkit, gathering relevant data on access to food and water, basic utilities, financial burden, household demographics, and safety. Four months after Sandy, electricity and heat had been restored to all households. However, around one-third of them still had difficulty in obtaining food, and about one-half believed that their neighborhood was unsafe. One-quarter had problems in acquiring prescription medications, and approximately one-half reported anxiety. While basic utilities were almost entirely restored, there were ongoing challenges in Rockaway four months after Sandy, relating to financial hardship, food insecurity, healthcare, and psychologic distress.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.359
GPT teacher head0.507
Teacher spread0.148 · 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 designObservational
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

Citations14
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueDisastersSame topicFood Security and Health in Diverse PopulationsFrench-language works237,207