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Record W2886848354 · doi:10.1080/09644016.2018.1507290

(De)legitimating extractivism: the shifting politics of social licence

2018· article· en· W2886848354 on OpenAlexafffundabout
Shane Gunster, Robert Neubauer

Bibliographic record

VenueEnvironmental Politics · 2018
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPoliticsSociologyAgency (philosophy)Social movementInjusticeDemocracyPolitical sciencePolitical economyState (computer science)LawLaw and economicsSocial science

Abstract

fetched live from OpenAlex

Most scholarly accounts of social licence define it as a public relations strategy to legitimate resource development. In Canadian pipeline politics, however, it has had the opposite effect, crystallizing widespread concerns about industry capture of regulatory processes and affirming the democratic rights of local communities. This assessment of the concept’s critical, counter-hegemonic potential to challenge the policies, practices and logic of state-sponsored extractivist development situates social licence as a key discursive battleground in the struggle between politicization (which accents agonistic confrontation between competing alternative futures) and de-politicization (which defuses conflict and builds consensus around the perception of common interests). Frame analysis of news media and advocacy group texts is used to investigate how opponents of a pipeline project bridged the idea of social licence with movement frames concerning identity, injustice and democratic agency to transform the concept from a public relations term meant to enable corporate activity into a critical trope used to constrain it.

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)0.011
metaresearch head score (Gemma)0.011
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 score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0110.086
Scholarly communication0.0140.010
Open science0.0010.010
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.008
GPT teacher head0.209
Teacher spread0.201 · 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

Citations36
Published2018
Admission routes3
Has abstractyes

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