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Record W4392817553 · doi:10.4314/jcas.v20i1.6

Science Advisory to Governments and Regional/Sub-Regional Organizations in West and Central Africa

2024· article· en· W4392817553 on OpenAlexfundno aff
David A. Mbah, Madiagne Diallo, Magellan Guewo‐Fokeng

Bibliographic record

Venue˜The œjournal of the Cameroon Academy of Sciences · 2024
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsRegional scienceGeographyPolitical science

Abstract

fetched live from OpenAlex

Science advice to governments and regional and sub-regional organizations in West and Central Africa has been reviewed. The objectives were to analyze its evolution and characterize the sources of advice. During the colonial period, it was by the colonial administrations and for their needs. At independence, in general, the new nations (particularly French speaking) entered into agreements with the former colonial powers to develop science, technology and innovation capacity for sustainable development. English speaking nations sought more partners outside the colonial experience. Colonial research institutes were increasingly transformed into national research institutes/institutions with national development mandates. Governments increasingly turned to science advice from consultants, inter- ministerial committees, advisory bodies, ad hoc experts’ groups, or a combination of these. Regional/sub-regional organizations sought advice from consultants, ad hoc technical experts’ groups, advisory bodies or a combination of these. Increasingly, science advice is delivered by Africans. Science advice by science academies is most rigorous. The arrival of more science academies, with varying links with governments, indicates that evidence-based science advice is growing in the region.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.272
Teacher spread0.253 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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Same venue˜The œjournal of the Cameroon Academy of SciencesSame topicBiotechnology and Related FieldsFrench-language works237,207