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Record W2540372183

Insecurity, Weak Health Systems and Poliomyelitis Eradication

2015· article· en· W2540372183 on OpenAlexaff
Nazia Sohani

Bibliographic record

VenueGlobal Health: Annual Review · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPoliomyelitisPoliomyelitis eradicationHealth careGlobal healthPolitical scienceDisease EradicationHealthcare systemEconomic growthDevelopment economicsMedicineVirologyEconomicsDiseasePoliovirusLaw
DOInot available

Abstract

fetched live from OpenAlex

This paper will explore how global efforts of polio eradication are defeated in fragile and conflict affected areas with weak health systems, such as Afghanistan and Pakistan. In addition the paper will investigate how conflict and political instability leads to resurfacing of poliomyelitis in countries where it was previously eliminate such as, Syria. Ultimately, this paper aims to answer the question what are the characteristics that strong healthcare systems entail in order to eradicate infectious diseases such as poliomyelitis. In addition, the paper aims to explore how weak health systems and conflict hinder the global poliomyelitis eradication efforts. A review of existing literature on healthcare systems, as well as media articles will be analyzed to gather data. Implications of failed poliomyelitis eradication initiatives on non-governmental organizations as well as on the global world are also included in this paper.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.130
GPT teacher head0.521
Teacher spread0.391 · 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
GenreReview

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
Published2015
Admission routes1
Has abstractyes

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