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Displaced persons' perceptions of human rights in Southern Sudan

2009· article· en· W2031181074 on OpenAlexaff
Carol Pavlish, Anita Ho

Bibliographic record

VenueInternational Nursing Review · 2009
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHuman rightsFocus groupContext (archaeology)Human securityGovernment (linguistics)Political scienceSociologyEconomic growthPublic relationsLawGeography

Abstract

fetched live from OpenAlex

BACKGROUND: A human rights framework has become more important in advancing equitable health and development opportunities. However, in post-conflict settings, human rights violations persist. Women and girls are especially vulnerable to discrimination and violence. AIM: To deepen understanding about the social context that influences human rights experiences and gender relationships in a post conflict setting. METHODS: Focus groups and key informant interviews were conducted in an ethnographic study among displaced persons, government officials and community-based organizations in Southern Sudan. FINDINGS: Participants defined human rights as the right to good governance, self-determination and participation in society's development, security and equality. Human rights violations included discrimination, insecurity and inadequate health and development opportunities. Education, language and geographic location influenced human rights perspectives. Some social groups were at higher risk for human rights violations. CONCLUSIONS: Community perspectives on human rights indicated complex connections between obligations, claims, conditions and social relationships. Nurses can create conditions that advance people's human rights and improve their health.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.998

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)0.0030.000

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 head0.026
GPT teacher head0.407
Teacher spread0.380 · 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 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

Citations9
Published2009
Admission routes1
Has abstractyes

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