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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.001
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: none
Teacher disagreement score0.814
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.015
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