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Record W2568726063 · doi:10.18192/uojm.v6i2.1558

The Effect of Conflict and Displacement on the Health of Internally Displaced People: The Colombian Crisis

2016· article· fr· W2568726063 on OpenAlexaffvenue
Juliana Andrea Barrera Ramirez, Hernan Dario Franco

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicConflict, Peace, and Violence in Colombia
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPolitical scienceInternally displaced personPopulationHumanitiesCriminologyRefugeeSociologyMedicineEnvironmental healthLaw

Abstract

fetched live from OpenAlex

ABSTRACTDecades of violence in Colombia led to the relocation of millions of rural families into urban areas, where the violation of human rights and abuse add to the struggle to meet most basic needs. Lack of housing, economic instability, poor access to healthcare and educa­tion impact their overall health. Unfortunately, implementation of laws created to alleviate the crisis has been unsuccessful, as armed groups target aid efforts through violence and threats. While the role of physicians is limited, advocacy and collaboration with other organizations can help improve the health and well-being of this population. RÉSUMÉDes décennies de violence en Colombie ont mené au relogement de millions de familles rurales vers des milieux urbains, où la viola­tion des droits de la personne et les sévices exacerbent la lutte pour subvenir aux besoins fondamentaux. Le manque de logement, l’instabilité économique, et l’accès restreint aux soins de santé et à l’éducation ont un impact sur leur santé globale. Malheureuse­ment, l’établissement de lois conçues pour alléger la crise s’est révélé sans succès, puisque des groupes armés ciblent ces efforts d’aide humanitaire avec de la violence et des menaces. Bien que le rôle des médecins soit limité, les activités de plaidoyer et la collaboration avec d’autres organismes peuvent aider à améliorer la santé et le bien-être de cette population.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.282
Teacher spread0.269 · 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.

Study designNot applicable
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

Citations9
Published2016
Admission routes2
Has abstractyes

Explore more

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