Perceived outcomes and SWOT analysis of a virtual community of practice in Burkina Faso
Bibliographic record
Abstract
Abstract Background In Burkina Faso, maternity is a risk. Global Affairs Canada funded the initiative PASME-2 with World University Service of Canada, Laval University and Farm Radio International to improve maternal outcomes. A preventative program was co-developed in phases. Phase 3 received funding from Social Sciences and Humanities Research Council in partnership with the Centre for International Cooperation in Health and Development (CCISD) and TIESS, a liaison and transfer expert in Québec, to support local teams towards sustainable practice changes. This research aimed at documenting the partnership experience, digital literacy, perceived direct and indirect outcomes. Methods A participative co-design approach, allowed the engagement of several stakeholders in the process. Two active phases where 16 health professionals engaged actively in the VCoP, according to the final agreed-upon Constitutional Chart, are presented. The phases pilot-tested two different technology tools. Results 16 interviews post-phase 1 and 16 interviews post-phase 2 were conducted. Implementation issues as perceived by users are discussed and include: feasibility, challenges, needs, animation, relevance to care, communication and sharing, use and perspectives. Perceived outcomes focus on professional preventative practice changes, skills, family outcomes, challenges to practice integration, knowledge and practice exchanges. Conclusions The phases of experimentation demonstrate that strategies can be put in place to counter the digital literacy challenges and to engage users in new ways of communicating, sharing on the platform about health practices and taking valuable time to do it. Overcoming technology constraints is essential especially in lower resource settings. The most practical life experiences and cases lead to more engagement and innovations. Support from management and upper directorate is significant. Key messages Partnership from several stakeholders is key to implementing a VCoP. Experimenting and sharing solutions is influenced by the capacitating environment that the VCoP can provide with recognition from administration and as a professional development activity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".