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Record W2792839681 · doi:10.1192/bji.2017.25

Resilience in Haiti: is it culturally pathological?

2018· article· en· W2792839681 on OpenAlexaff
Daniel Dérivois, Jude Mary Cénat, Amira Karray, Nathalie Guillier-Pasut, Jeff Matherson Cadichon, Baptiste Lignier, Nephtalie Eva Joseph, Lisbeth Brolles, Yoram Mouchenik

Bibliographic record

VenueBJPsych International · 2018
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsResilience (materials science)Face (sociological concept)Psychological resiliencePopulationHistoryGeographyPolitical scienceSociologyPsychologyDemographySocial scienceSocial psychology

Abstract

fetched live from OpenAlex

Not for the first time in recent history, the people of Haiti have been obliged to fall back on their resilience strategies in the aftermath of Hurricane Matthew. Following the powerful earthquake that struck the country on 12 January 2010, the entire population had to find the resources to survive in the face of extensive material damage and loss of life: over 222 000 dead, more than 300 000 injured and between 4000 and 7000 amputees (UNDP, 2010).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0110.004

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 head0.058
GPT teacher head0.455
Teacher spread0.398 · 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; both teacher heads agree on what is shown here.

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

Citations12
Published2018
Admission routes1
Has abstractyes

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