MétaCan
Menu
Back to cohort
Record W2901644049 · doi:10.1186/s12961-018-0388-8

A deliberative dialogue as a knowledge translation strategy on road traffic injuries in Burkina Faso: a mixed-method evaluation

2018· article· en· W2901644049 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHealth Research Policy and Systems · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsMontreal Clinical Research InstituteUniversité de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsKnowledge translationThematic analysisGovernment (linguistics)Public relationsAction planQualitative propertyCivil societyAction (physics)Political scienceData collectionPlan (archaeology)Descriptive statisticsPoliticsQualitative researchMedical educationKnowledge managementSociologyMedicineComputer scienceManagementGeographySocial science

Abstract

fetched live from OpenAlex

INTRODUCTION: Deliberative dialogues are increasingly being used, particularly on the African continent. They are a promising interactive knowledge translation strategy that brings together and leverages the knowledge of diverse stakeholders important to the resolution of a societal issue. Following a research project carried out in Burkina Faso on road traffic injuries, a 1-day workshop in the form of a deliberative dialogue was organised in November 2015. The workshop brought together actors involved in road safety, such as researchers, police and fire brigades, health professionals, non-governmental and civil society organisations, and representatives of government structures. The objective was to present the research results, propose recommendations to improve the situation and develop a collective action plan. METHOD: To better understand the workshop's utility and effects, a mixed-method evaluation was conducted. Data were obtained from two questionnaires distributed at the end of the workshop (n = 37) and 14 qualitative interviews with participants 6-10 weeks after the workshop. Descriptive statistics were used to analyse the quantitative data, and a thematic analysis was conducted for the qualitative data. RESULTS: The data revealed several positive impacts of the workshop, such as the acquisition of new knowledge about road safety, the opportunity for participants to learn from each other, the creation of post-workshop collaborations, and individual behaviour changes. However, several challenges were encountered that constrained the potential effects of the workshop, including the limited presence of political actors, the lack of engagement among participants to develop an action plan, and the difficulty in setting up a monitoring committee following the workshop. CONCLUSION: While the deliberative workshop is not the standard format for reporting research results in Burkina Faso, this model should be reproduced in different contexts. This interactive knowledge translation strategy is useful to benefit from the experiential knowledge of the various actors and to encourage their involvement in formulating recommendations.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.087
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0870.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
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 head0.865
GPT teacher head0.747
Teacher spread0.118 · 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