Youth agency in times of crisis: Exploring education and conflict in Mali through participatory visual approaches with youth
Bibliographic record
Abstract
Education in Mali is constrained by a multi-dimensional crisis that restricts education and makes life difficult. Young people are particularly affected. In this article, we use the preliminary findings of the Participatory Research on Education and Agency in Mali (PREAM) project that was implemented in the conflict-affected regions of Mopti and Segou, to discuss youth agency in situations of crisis and how participatory visual methods can be used both as a way of ascertaining adolescents’ perception of their agency and also to contribute to the development of youth agency. More specifically, we use data from six workshops using participatory visual methods (PVMs) to illustrate that young people have something valuable to say about education, agency, and conflict and that PVMs can be an effective way of engaging adolescents in dealing with such topics. Preliminary findings from the research suggest that although participating young people are in an asymmetrical position in relation to power with the adults around them, they nonetheless have a good understanding of their situation and demonstrate agentic behavior that is both adaptative and projective. Girls illustrated how generational order from child to grandmother and gender social norms can constrain agency. At the same time, they used their agency to expose and contest, in the cellphilms they produced, the unfair division of labor in their society. During the workshops, young people were eager to share their stories and wanted their artwork to communicate their concerns to the adults around them. In this article, we argue that it is important for adolescents in Mali to have a voice on questions of education and agency and we discuss why education actors and policy makers should pay attention to the perspectives of young people even (and especially) in times of crisis.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".