Review: Environmentality: Technologies of Government and the Making of Subjects by Arun Agrawal
Bibliographic record
Abstract
EGJ Issue 26 Spring 2008 ISSN 1076-7975 Review: Environmentality: Technologies of Government and the Making of Subjects By Arun Agrawal Reviewed by Jeff Shantz Kwantlen University College, Vancouver, B.C. Arun Agrawal. Environmentality: Technologies of Government and the Making of Subjects. Durham, N.C.: Duke University Press, 2005. 325 pp. ISBN: 0-8223-3492-5. US $22.95 paper. Acid-free paper. In the early 1920s the villagers of Kumaon in northern India set hundreds of forest fires to protest the colonial British state's environmental regulations. By the 1990s these village communities had become careful and persistent conservators of the forests. This transformation in thinking and practice provides the starting point for Arun Agarwal's compelling and theoretically challenging analysis of environmental agency. Agrawal's study identifies a key aspect in the development of environmental identities and behaviors in the shift from centralized to decentralized decision-making with the communities in Kumaon and between the communities and the government. The author demonstrates the rich analytical possibilities that might be developed through an engagement of thinking on political ecology with scholarship on common property and feminist environmentalism. The approach that emerges from such an engagement, what Agarwal calls environmentality, can help to contribute to a fuller understanding of transformations in environmental thought and practices of conservation. Bringing together a concern with power/knowledge, institutional arrangements and human subjectivities, the approach to environmentality calls upon Foucault's post-structuralist work to explain the development of environmental subjects and practices that govern their activities. As Agarwal demonstrates, changes in the relationships between states, community decision makers and non-elite residents contribute to the emergence of new technologies of government, in terms of environmental regulation, the implementation of which is in turn variously contested. What is perhaps most striking about Agrawal's work is the extensive character of his research. The author spent time in almost forty villages in Kumaon, interviewing hundreds of residents and personally examining the condition of village forests. His fieldwork was supplemented with archival research into local records to obtain a clear sense of changes in the relations between states and localities over time. The most significant conclusion is the importance of decentralization and the dispersal of decision-making power and its impacts on relations between states and local communities, community leaders and non-elite residents. Of particular note is the Electronic Green Journal , Issue 26, Spring 2008 ISSN: 1076-7975
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".