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Record W2795116464 · doi:10.1097/phh.0000000000000721

Accreditation's Role in Bolstering Resilience in the Face of the Zika Virus Outbreak

2018· article· en· W2795116464 on OpenAlexaff
Celeste Philip, Kelli T. Wells, Russell Eggert, Jennifer Elmore, Reynald Jean, Jennifer Johnson, Jeanne Lane, Ximena López, Lillian Rivera, Elmir Samir, Natasha Strokin, Yesenia Villalta, Rene Ynestroza

Bibliographic record

VenueJournal of Public Health Management and Practice · 2018
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsTransAlta (Canada)
Fundersnot available
KeywordsAccreditationPublic healthHealth departmentMiamiEnvironmental healthMedicinePolitical scienceMedical educationNursing

Abstract

fetched live from OpenAlex

The Florida Department of Health (Department) received accreditation status as an integrated public health system from the Public Health Accreditation Board (PHAB) in 2 phases: the State Health Office received accreditation in June 2014 and the 67 county health departments received accreditation in March 2016. Six weeks after PHAB awarded accreditation to the Department as an integrated public health system in March 2016, the World Health Organization declared the Zika outbreak in the Americas a Public Health Emergency of International Concern. Even in that short time, integrated public health accreditation, along with the other components of the Department's performance management system, allowed the Department to address this public health emergency, especially in Miami-Dade County, where the impact of Zika was significant. This case report describes the local response in Miami-Dade County and supporting statewide efforts. Public health departments should consider how public health accreditation could strengthen their ability to fulfill their public health mission. This article provides rationale for state and local health departments to seek accreditation.

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)0.005
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.167

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 head0.048
GPT teacher head0.368
Teacher spread0.320 · 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 designOther design
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

Citations6
Published2018
Admission routes1
Has abstractyes

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