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Record W2969496237

Advocating for a Home-State Grievance Mechanism: Law Reform Strategies in the Canadian Resource Justice Movement

2018· article· en· W2969496237 on OpenAlexaffabout
Charis Kamphuis

Bibliographic record

VenueSSRN Electronic Journal · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Law and Human Rights
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsGrievancePolitical scienceLaw reformGovernment (linguistics)Human rightsEconomic JusticePoliticsCivil societyPublic administrationLaw
DOInot available

Abstract

fetched live from OpenAlex

The vast majority of mining companies operating globally are Canadian. For nearly two decades, social justice advocates systematically documented the concerns of mine-affected communities in relation to Canadian operations in developing countries, producing a significant body of empirical work that described not only the nature of the social conflicts associated with Canadian companies but also the mechanisms whereby the Canadian government provides companies with political, economic and legal support. Beginning in 2005, activists, policy makers, industry leaders and international human rights bodies participated in a sustained debate over the appropriate Canadian regulatory responses to these issues. This chapter analyses the strategies of law reform advocates between 2000 and 2017 to critique Canadian policy and the overseas conduct of Canadian extractive companies. It gives special attention to the 2016 law reform proposal from Canadian civil society, the draft Business & Human Rights Act. The strategies profiled here are of special interest because they resulted in a significant, if not unexpected, breakthrough in early 2018 when the Canadian government announced a globally unprecedented new grievance mechanism: the Canadian Ombudsperson for Responsible Enterprise. The discussion is of interest to those concerned with law's potential (and limitations) as an instrument of social justice in the global economy, and particularly for communities affected by foreign resource extraction.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.227
Teacher spread0.213 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2018
Admission routes2
Has abstractyes

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