MétaCan
Menu
Back to cohort
Record W2135703731 · doi:10.1177/0309132507077080

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

2007· article· en· W2135703731 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProgress in Human Geography · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsYork University
Fundersnot available
KeywordsGovernmentalityBiopowerSociologyEpistemologyHuman geographyAnalyticsPower (physics)Reading (process)Through-the-lens meteringMichel foucaultScale (ratio)Social scienceData sciencePolitical sciencePoliticsLens (geology)LawComputer scienceGeographyPhilosophyCartography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.353
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it