Appréhender les conceptions locales de l'équité pour formuler les politiques publiques de santé au Burkina Faso
Bibliographic record
Abstract
Equity is an essential health promotion concept and must be included at the heart of public health policy making. However, equity, which can also be referred to as social justice, is a polysemic and contextual term which definition must stem from the discourse and values of the society where the policies are implemented. Using a case study from Burkina Faso, we try to show that the non-acknowledgement of the local concept of social justice in the policy making process partly explains the resulting policies' relative failure to achieve social justice. Data collection methods vary (individual and group interviews, concept mapping, participant observation, document analyses) and there are qualitative and quantitative analyses. The four groups of actors who generally participate in the policy making process participated in the data collection. With no intention to generalise the results to the entire country, the results show that mass social mobilisation for justice is egalitarian in type. Health or social inequalities are understood by individuals as facts which we cannot act upon, while the inequalities to access care are qualified as unjust, and it is possible to intervene to reduce them if incentive measures to this effect are taken. We also observed a certain social difficulty to conceive sub-groups of population and fierce will to not destabilise social peace, which can be provoked when looking for justice for the impoverished sectors of the population. This research allows better understanding about the emic aspect of equity and seems to confirm the importance of taking into account local values, especially social justice, when determining public policy.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".