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Record W2150833104 · doi:10.15171/ijhpm.2014.128

Ebola treatment and prevention are not the only battles: understanding Ebola-related fear and stigma

2014· article· en· W2150833104 on OpenAlexaff
Mohammad Karamouzian, Celestin Hategekimana

Bibliographic record

VenueInternational Journal of Health Policy and Management · 2014
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsKwantlen Polytechnic UniversityUniversity of British Columbia
Fundersnot available
KeywordsStigma (botany)Ebola virusMedicineEnvironmental healthVirologyFamily medicineCriminologyMedical emergencyPsychiatryPsychologyOutbreak

Abstract

fetched live from OpenAlex

Although Ebola Virus Disease (EVD) had already taken hundreds of lives in Liberia, Guinea, and Sierra Leone, it was only declared an 'Public Health Emergency of International Concern' in early August when the world started to panic from the possibility of EVD getting out of African borders -a fear that was spreading much faster than the virus itself (1,2). The underlying causes of this fear, however, go far behind the uncertainties surrounding EVD's pathogenesis and could stem from the past (3). The western perception of associating West Africa with deadly diseases such as malaria, yellow fever and EVD, and representing the region as white man's grave is not just fueled by superstition or ignorance and has roots in history For instance, the yellow fever outbreak in Liberia in the 20s that led to the loss of several prominent American and British medical researchers and instructors, has left the West with painful memories of the region (3). Regardless of past memories, while the transmission mechanism of Ebola is clear, there are irrational fears and overreactions globally. In the United States (U.S.) for example, school officials in New Jersey banned students coming from Rwanda (which is 1,700 miles away from the exposed region) from attending school unless after 21 days of quarantine (5). Similarly, some colleges in Texas rejected applications coming from Nigeria (6). Reports of flight suspensions to the area and imposing restrictions as well as visa denials for those coming from the region have also been ubiquitous (7). Unfortunately, these rejections and shunning behaviours have not only targeted some of the African nations, but have also affected western healthcare providers in close proximity with the patients in quarantine settings in U.S. hospitals (8). On the other hand, fear also exists in West Africa where the local African communities may have concerns and mistrust about the spread of the disease and the western led investigations in their countries. This face of the fear has also deep roots in the past and can be elaborated upon by getting back to our history lesson of the former mentioned yellow fever outbreak in Liberia. When American research teams were sent to the region to collect samples and study the disease, they scared off the locals by using the routes used by European and West

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.204

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 studies0.0000.000
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 head0.085
GPT teacher head0.427
Teacher spread0.342 · 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

Citations63
Published2014
Admission routes1
Has abstractyes

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