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Record W2922373660 · doi:10.1017/s2071832200017909

Home State Regulation of Environmental Human Rights Harms As Transnational Private Regulatory Governance*

2012· article· en· W2922373660 on OpenAlexaffabout
Sara L. Seck

Bibliographic record

VenueGerman Law Journal · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Law and Human Rights
Canadian institutionsWestern University
Fundersnot available
KeywordsJurisdictionCorporate governanceTransnational governanceHuman rightsState (computer science)Political scienceRegulatory stateInternational lawInternational human rights lawLaw and economicsBusinessPublic administrationLawEconomicsFinance

Abstract

fetched live from OpenAlex

Home state mechanisms designed to address harms arising from overseas resource extraction have recently been considered in Canada. This paper will examine whether such mechanisms could be viewed as an example of transnational private regulatory governance, and the implications of doing so for our understanding of both public international law and transnational private regulatory governance. After first briefly unpacking the idea of transnational private regulatory governance, the paper will compare common understandings of the scope of home state jurisdiction to regulate transnational corporations under international human rights and international environmental law. Recent developments in Canadian law and policy culminating in the creation of a Corporate Social Responsibility (CSR) Counsellor for the international operations of the Canadian extractive industry will then be described. This Canadian experience will serve an example of home state-based transnational private regulatory governance.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.382
Threshold uncertainty score0.759

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0070.039
Scholarly communication0.0100.005
Open science0.0020.007
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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 designNot applicable
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

Citations17
Published2012
Admission routes2
Has abstractyes

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