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Unpacking capacity to utilize research: A tale of the Burkina Faso public health association

2010· article· en· W2089973959 on OpenAlexafffund
Nadia Hamel, Ted Schrecker

Bibliographic record

VenueSocial Science & Medicine · 2010
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of OttawaInstitute of Population and Public Health
FundersInternational Development Research CentreUnited Nations Development ProgrammeUniversity of Ottawa
KeywordsKnowledge translationCapacity buildingKnowledge managementLeverage (statistics)Public relationsFlexibility (engineering)Public healthBusinessPolitical scienceMedicineComputer scienceNursingManagementEconomics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.099
metaresearch head score (Gemma)0.122
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.524

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0990.122
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0280.074
Scholarly communication0.0290.034
Open science0.0020.023
Research integrity0.0170.026
Insufficient payload (model declined to judge)0.0060.001

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 head0.758
GPT teacher head0.696
Teacher spread0.062 · 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.

Study designQualitative
DomainIncentives
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

Citations34
Published2010
Admission routes2
Has abstractno

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