MétaCan
Menu
Back to cohort
Record W2916753431 · doi:10.1177/0170840618815928

Saving the Canadian Fur Industry’s Hide: Government’s strategic use of private authority to constrain radical activism

2019· article· en· W2916753431 on OpenAlexaffabout
Johnny Boghossian, José Carlos Marques

Bibliographic record

VenueOrganization Studies · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsUniversity of OttawaUniversité Laval
Fundersnot available
KeywordsConceptualizationGovernment (linguistics)PoliticsStakeholderTransnational governancePublic administrationPolitical economySociologyPolitical sciencePublic relationsLaw

Abstract

fetched live from OpenAlex

We examine the relationship between private and public regulatory authority in contexts characterized by radical transnational activist contestation against industry practices. Employing a comparative case design, we study government responses to similar activist campaigns calling for a trade ban on Canada’s sealing and fur industries. Relying on conventional public authority, the Canadian government was unable to prevent a European ban on seal skin products, leading to the collapse of its sealing industry. In contrast, its response to anti-fur trapping activists successfully employed private authority in the form of a standard-setting multi-stakeholder initiative (MSI). Doing so not only averted a ban but effectively shut down international debate over restrictions concerning the sale of products using trapped fur. Drawing from social movement theory on activist heterogeneity and political opportunity structure, we introduce a novel conceptualization of standard-setting MSIs as strategic instruments employed by governments to constrain the political opportunities for radical transnational activists. Our findings contribute to the literatures examining interactions between private and public regulatory authority, instruments of government repression and the political dynamics surrounding MSIs.

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 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)0.000
metaresearch head score (Gemma)0.001
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 score0.086
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.060
GPT teacher head0.280
Teacher spread0.220 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations37
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueOrganization StudiesSame topicGlobal trade, sustainability, and social impactFrench-language works237,207