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Cited by 391

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Green governmentality: insights and opportunities in the study of nature's rule

Rutherford, Stephanie·2007·Progress in Human Geography

Abstract

This article seeks to unpack notions of governmentality by reading it through the case of nature. By highlighting three key aspects of governmentality — its analytics of power, biopolitics, and technologies of the self — I argue that this approach presents a promising theoretical trend for those who study nature and its rule. However, there have been critiques leveled at this approach which must be considered. Using examples drawn from human/non-human interactions, I explore how the governmentality literature needs to be made more complex and attune to difference. In the final analysis, I argue that the concept of governmentality is not only an effective tool for geographers, but that geography provides a particularly insightful lens with its attention to spatiality, scale, territory and human/non-human relations that enrich the analysis of the making of governable spaces.

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Metadata

Authors
Rutherford, S.
Venue
Progress in Human Geography
Published
2007-06
Volume
31
Issue
3
Pages
291-307
ISSN
  • 0309-1325 (ISSN-L)
  • 1477-0288
OpenAlex
W2135703731
Cited by
391
References
35
FWCI
36.13
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Green governmentality: insights and opportunities in the study of nature's rule. https://app.cochat.ai/papers/10.1177/0309132507077080
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Rutherford, S. (2007). Green governmentality: insights and opportunities in the study of nature's rule. Progress in Human Geography. https://doi.org/10.1177/0309132507077080

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.