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Record W6991550255

Hurricanes Katrina and Rita: Unprecedented Challenges Exposed the Individuals and Households Program to Fraud and Abuse; Actions Needed to Reduce Such Problems in Future

2011· other· en· W6991550255 on OpenAlexfundno aff

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2011
Typeother
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
FundersFederal Emergency Management AgencyMcGill UniversityU.S. Department of Homeland Security
KeywordsHurricane katrinaGovernment (linguistics)Vulnerability (computing)AccountabilityEmergency managementNatural disasterLocal government
DOInot available

Abstract

fetched live from OpenAlex

A letter report issued by the Government Accountability Office with an abstract that begins "In 2005, Hurricanes Katrina and Rita caused unprecedented damage. The Federal Emergency Management Agency's (FEMA's) Individuals and Households Program (IHP), provides direct assistance (temporary housing units) and financial assistance (grant funding for temporary housing and other disaster-related needs) to eligible individuals affected by disasters. Our objectives were to (1) compare the types and amounts of IHP assistance provided to Hurricanes Katrina and Rita victims to other recent hurricanes, (2) describe the challenges FEMA faced by the magnitude of the requests for assistance following Hurricanes Katrina and Rita, and (3) determine the vulnerability of the IHP program to fraud and abuse. GAO determined the extent to which the program was vulnerability to fraud and abuse, by conducting statistical sampling, data mining and undercover operations."

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.102
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.1020.032

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 head0.024
GPT teacher head0.212
Teacher spread0.188 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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