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Record W2766117827 · doi:10.3897/rio.3.e21700

Case Study: Neglected Health Issues in Niger

2017· article· en· W2766117827 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResearch Ideas and Outcomes · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsDisadvantagedHealth careDecentralizationPolitical scienceHealth policyReproductive healthCorporate governanceNursingPublic relationsMedicineBusinessEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

The project “Problemes négligés du système de santé au Niger” focusses on a core set of often-neglected issues that nevertheless have an overall negative impact on health system effectiveness in Niger. For example, poor quality maternal health services result from challenges related to the midwifery profession and from pressures from addressing the effects of illegal termination of pregnancy. Overall health system governance is undermined by weak management of human resources and health information systems as well as problems related to decentralisation of health care provision and dependence on external funding for health projects. LASDEL applies a rapid assessment and qualitative research approach to working with patients and health care professionals to identify the scale and characteristics of these problems. The project goal is to develop an evidence base to support tackling these neglected issues. Développer des recherches sur les « problèmes négligés » dans la gouvernance de la santé, et sur cette base contribuer à des réformes des systèmes de santé permettant une meilleure qualité des soins pour les populations vulnérables. "Develop research on "neglected problems" in the provision of health systems, and through this work, contribute to health system reforms, that provide better quality of care for vulnerable populations." As can be seen above, many of these issues relate to reproductive health and more generally to health issues of disadvantaged groups. Some issues are neglected for political or social reasons meaning that they are not recognised or acknowledged and in some cases are criminalised. Therefore there are profound issues of participant privacy, protection and even safety for this project. Data sharing therefore requires thoughtful anonymisation and selection. The project group is Francophone with limited English language knowledge and the researchers and the context is largely in French. In common with much of Francophone Africa there has been limited development of Open Access to research outputs or Open Research Data agendas at governmental or funder levels. Outside of Canada and France there has been limited development of infrastructure, systems or policy relating to data sharing in the global francophonie specifically.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.936

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 studies0.0010.000
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 head0.121
GPT teacher head0.512
Teacher spread0.390 · 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