MétaCan
Menu
Back to cohort
Record W2783164600 · doi:10.1192/s1749367600005737

Mental health in the Democratic Republic of Congo: a post-crisis country challenge

2010· article· en· W2783164600 on OpenAlexaff
Michel Okitapoy On'okoko, Rachel Jenkins, Samuel Mampunza Ma Miezi, Daniel Okitundu Luwa E Andjafono, Ildephonse Muteba Mushidi

Bibliographic record

VenueInternational Psychiatry · 2010
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsMcGill University
Fundersnot available
KeywordsDemocracyLegislationPoliticsPolitical scienceMental healthPolitical crisisDevelopment economicsEconomic growthGeographyMedicineLawPsychiatryEconomics

Abstract

fetched live from OpenAlex

The delivery of mental healthcare in the Democratic Republic of Congo (DRC), formerly Zaire, is influenced by geography, politics, legislation and the structure of the health system, as well as traditional beliefs and culture.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0070.005
Open science0.0010.007
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.017
GPT teacher head0.371
Teacher spread0.354 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations31
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueInternational PsychiatrySame topicMental Health Treatment and AccessFrench-language works237,207