The Role of Traditional Ecological Knowledge in Education for Community-Based Resource Management
Bibliographic record
Abstract
"Globalization, like colonialism, homogenizes and generalizes knowledge and practice. Formal systems of education are one of the most powerful tools in the process. They are both liberating and constraining. Some of the effects of globalization in terms of knowledge and practice run counter to the more particular and local needs for sustainable environmental and resource management. The issue to be addressed in this paper is that of bridging the enormous gap between the forces of globalization and effective community-based resource management through the medium of formal education, supplemented by informal education and traditional ecological knowledge. Traditional ecological knowledge is by definition place specific and, as such, may balance some of the homogenizing and generalizing effects of globalization. \n \n "The generalizing effects of formal education as a tool of colonialism was well recognized by the likes of Gandhi and Nyerere and gave rise to their respective Basic Education and Education for Self-Reliance, components of their post-colonial visions. Each called into play variants and elements of local and traditional ecological knowledge. Community-based resource management approaches and experience, particularly with respect to common property resources, provide examples where local and particular foci can come into play effectively. One of the consequences of globalization and the attendant systems of education has been the loss or marginalization of traditional ecological knowledge, the associated knowledge systems, their practitioners and traditions and vernacular languages which are sensitive to local biodiversity (Berkes, 1999). \n \n "We argue that this need not be and that it may be detrimental to sustainable resource management. To illustrate the point, three examples from India are described and discussed. The examples provide evidence for the effective use of traditional ecological knowledge in community-based resource management and raise implications for formal systems of education. Biodiversity contests for school-age children, some of whom may be short-lived school goers, in rural Gujarat and Maharashtra demonstrate a rich, largely untapped and marginalized resource present in the community. Gram Vidyapiths or rural degree colleges in Gujarat, founded on the Gandhian model of basic education provide an example within the formal structure of education where local and traditional ecological knowledge can be used to address community resource management needs. The Medicinal Plant Conservation Centre, headquartered in Pune, Maharashtra provides several instances whereby traditional ecological knowledge may be valued and used effectively in community-based resource management."
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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 | 0.004 | 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 | 0.021 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".