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Record W1503649356 · doi:10.1108/17542431211264287

Political risk insurance, CSR and the mining sector

2012· article· en· W1503649356 on OpenAlexaff
Kernaghan Webb

Bibliographic record

VenueInternational Journal of Law and Management · 2012
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCorporate social responsibilityTransparency (behavior)BusinessContext (archaeology)Value (mathematics)OriginalityPoliticsRisk managementAccountingPublic relationsFinancePolitical science

Abstract

fetched live from OpenAlex

Purpose The aims of this paper are: to explore the nature of political risk insurance (PRI) contracts as a form of regulation in the context of mining projects in developing countries; to examine how PRI providers factor corporate social responsibility (CSR) policies and practices of applicants in their initial decisions to provide PRI; to examine how CSR criteria are reflected in the terms of PRI contracts; to understand how failure to exercise good CSR practices by recipients of PRI affects insurance coverage; to shed light on how good CSR practices which minimize risk to companies and communities can be or are rewarded through PRI contracts; to identify opportunities for reform. Design/methodology/approach This article adopts a conceptual approach through analysis of the practical effects and public policy implications associated with use of PRI contracts as a regulatory mechanism to promote good CSR practices. Findings PRI contracts represent a form of proactive risk management used by investors. Because of the significant regulatory effect of the CSR provisions of PRI contracts provided by state‐based agencies, there is considerable potential for and value associated with greater transparency in the implementation of such contracts. Originality/value This article sheds light on the regulatory dimensions associated with the CSR provisions of PRI contracts. This represents a new contribution to the literature on CSR contracts, which until this point has focused largely on the CSR aspects of supply chain contracts.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.977
Threshold uncertainty score0.163

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.008
GPT teacher head0.222
Teacher spread0.214 · 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 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

Citations14
Published2012
Admission routes1
Has abstractyes

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