Navigating a polycrisis: barriers to maternal healthcare access in Burkina Faso
Bibliographic record
Abstract
Burkina Faso exemplifies a polycrisis, where overlapping sociopolitical, health, security and environmental disruptions collectively undermine public health progress. Despite decades of advancement in maternal and reproductive healthcare – through policies like fee abolition and expanded health facilities – recent crises have severely eroded these gains. Since 2014, Burkina Faso has faced escalating insecurity, becoming the world’s most terrorism-affected country, compounded by political instability following the ousting of long-time president Blaise Compaoré, repeated coups and increasingly militarized regimes. Simultaneously, the nation is grappling with deep economic inequality, environmental degradation and the lingering effects of the COVID-19 pandemic. These intertwined crises disproportionately impact the most vulnerable, deepening healthcare inequities. Emerging research highlights how this converging crisis landscape threatens access to quality maternal care, jeopardizing two decades of progress. Recognizing the polycrisis as a public health threat is critical to safeguarding maternal and reproductive health achievements in Burkina Faso and developing more resilient health systems amid compounded adversities.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".