Self-organization, linkages and drivers of change : strategies for development in Nuevo San Juan, Mexico
Bibliographic record
Abstract
This thesis analyzes the characteristics of community-based management systems to promote both environmental conservation and rural development.in particular, community structures for self-organization and adaptation, and their evolution in relation to changing community perspectives and policy trends.The community-based forest management system of Nuevo San Juan, Michoacán, Mexico, which is more than two decades old, is the central case study.Through the exploration of structures of self-organization, and the identification and analysis of cross-scale linkages and drivers of change, I explore the case in some depth and provide details on the beginning, management trends and evolution of the communal appropriation of resources.During a period of close to three months, using methods inspired by Participatory Rural Appraisal (PRA), field data were gathered through approximately one hundred field interviews with community members and others linked to the case.San Juan's intr¡cate management system includes the exploitation of timber and non{imber forest products through a communal enterprise.Community members of San Juan came together to create a communal management system to solve their local socio-economic problems.The community, unlike many others in Michoacán and Mexico, has been able to maintain the forest resource base and contribute to the generation of employment and socio-economic development in the municipality.New leadership trends and exogenous factors, however, are mod¡fying management processes and previously established trends.The findings indicate that enabling federal legislation, together with leadership and social capacity, can and do contribute to commun¡ty self-organization.Moreover, linkages at various levels help to strengthen and consolidate community-based management systems and increase their capacity for adaptation to deal w¡th pressure from external drivers.ln add¡tion, the findings suggest that a high level of system resilience, clear institutional and organizational structu[es, and proper government recognition and legal jurisdiction are not sufficient conditions for a successful communal management system.Other conditions, such as the application of core cultural and other values at the individual, community and institutional levels are also necessary to maintain community well- being and cohesion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".