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Record W4221049406 · doi:10.1080/14747731.2022.2054511

Two tiers and double standards: foreign investors and the local community of La Guajira, Colombia

2022· article· en· W4221049406 on OpenAlexaff
Federico Suárez Ricaurte

Bibliographic record

VenueGlobalizations · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsMcGill UniversityYork University
FundersStanford Law SchoolGlobal Challenges Research Fund
KeywordsMultinational corporationScope (computer science)Investment (military)Foreign direct investmentBusinessArbitrationScale (ratio)State (computer science)Capital (architecture)International tradeEconomicsMarket economyLawFinancePolitical sciencePoliticsGeography

Abstract

fetched live from OpenAlex

Under international investment law (IIL), multinational companies enjoy a broad protection of property and investment. They can sue through investment arbitration and claim compensation for any act of the host state that presumably affects their interests. In contrast, local communities that live around large-scale mining sites are often adversely affected by multinational companies and IIL itself. They are protected by domestic law and human rights frameworks, but their claims are limited in scope, reparations and effectiveness. This denotes the existence of two tiers and double standards system, with the interests of private foreign actors and their capital placed above the needs of local communities. In this article, I utilize a large-scale coal mining project in Colombia, the Cerrejón project, as a case study to illustrate the multiple ways in which IIL is implicated in the relations between the State, the foreign investor and the local community.

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)0.001
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.001
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 head0.015
GPT teacher head0.245
Teacher spread0.230 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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