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Record W1530472951 · doi:10.29173/cjs10127

Bourdieu in the North: Practical Understanding in Natural Resource Governance

2013· article· en· W1530472951 on OpenAlexafffundvenueabout
Ken J. Caine

Bibliographic record

VenueThe Canadian Journal of Sociology · 2013
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Alberta
FundersPierre Elliott Trudeau Foundation
KeywordsSociologyNegotiationCorporate governancePoliticsNatural resource managementEnvironmental governanceEnvironmental ethicsNatural resourceResource (disambiguation)Government (linguistics)EthnographyPower (physics)Natural (archaeology)Social sciencePolitical scienceEconomicsLawManagementAnthropology

Abstract

fetched live from OpenAlex

Natural resource management (NRM) analyses often avoid understanding environmental governance as arising from and shaped by social practices and power relations in resource conflicts, contested property rights, and political-economic strategies. I examine a northern Canadian Aboriginal community’s experience of a structured yet dynamic socio-cultural response to a period of social and political change. Drawing from Pierre Bourdieu’s conception of social practice I suggest that a diffuse, or less-determinist, theory of practice may help explain how power relations are interwoven throughout yet applied differentially in NRM governance. Drawing on ethnographic research on northern watershed management and protection of Aboriginal cultural landscapes, I propose the notion of practical understanding to explain the ways government resource managers and community leaders challenge and negotiate one another’s conceptions of environmental governance in a duel process of cooperation-conflict.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.466
Threshold uncertainty score0.938

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0190.117
Scholarly communication0.0110.008
Open science0.0020.006
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.090
GPT teacher head0.376
Teacher spread0.287 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2013
Admission routes4
Has abstractyes

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