In Search of Community: A Comparative Case Study of Education-for-development and Local Community Ownership in Chile and Central Africa
Bibliographic record
Abstract
Education evokes a powerful promise in development discourses. However, the role of local communities within these discourses has been unclear––often either romanticized or relegated to a passive context. In this comparative case study, I examine the role that local communities play in two transnational education-for-development projects: in the national capital region of the Central African Republic (CAR) and in the Williche territories of Chiloé, in Southern Chile. I examine the limitations of predominant theories of education in development and indicate how concepts of development are being redefined by populations and communities reading their own material, social, and spiritual realities in a given time and place. I draw on concepts from community studies and social solidarity to conceptualize “community” along several dimensions: place, structure and process, meaning, and time. To these, I suggest an additional dimension of capacity for protagonism. Empirically, I employ ethnographic and participatory methods in this study, building on participatory program evaluations solicited from funding partners in Luxembourg and Canada. I analyze the cases comparatively along three axes: horizontal, vertical, and transversal. Data from this study illustrate multifaceted ways that local communities respond to distinct conditions. Communities express ownership, capacity, and agency in the CAR in the midst of civil conflict to raise a network of community schools from grassroots neighbourhood and village settings. In Chiloé, communities prioritize the resurgence of Indigenous patterns of community life and systems of knowledge. In these two contexts, communities re-evaluate and reform curriculum and pedagogy according to local frameworks and exigencies: gradually in the case of the CAR, and through the creation of entirely new curriculum and pedagogical approaches in Chiloé. In conclusion, my findings indicate the importance of shifting conceptions of community away from a passive context to that of a protagonist in education-for-development discourses. The cases in this study illustrate how, when empowered through the development of capacities and abilities, communities stimulate educational development according to distinct needs, exigencies, and conceptual frameworks. As protagonists of their own paths of development, communities employ education to mobilize other vital community processes including agricultural development, cultural production, family health, and environmental protection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".