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Record W2164592716 · doi:10.1111/area.12183

Displacement and denationalisation: the<scp>M</scp>exican<scp>G</scp>ulf 75 years after the expropriation

2015· article· en· W2164592716 on OpenAlexafffund
Michelle Arroyo, Anna Zalik

Bibliographic record

VenueArea · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaConsejo Nacional de Ciencia y TecnologíaYork University
KeywordsRestructuringExpropriationPetroleum industryCommodityEconomicsBusinessEconomyMarket economyFinanceEngineering

Abstract

fetched live from OpenAlex

Recent oil and gas sector reforms in M exico transform protections on petroleum resources and labour that were implemented as a result of the 1938 nationalisation of the country's oil industry. This paper examines the E tileno XXI project, a private petrochemical plant led by a B razilian firm and supported by M exican and transnational capital, which manifests the role of early 21st‐century global commodity markets in restructuring M exico's energy sector. E tileno XXI is described as a major step toward privatising petrochemical processing in the country and as a significant creator of jobs, albeit low wage, at the site of production. Yet the project and corresponding oil‐sector reforms will have impacts on the surrounding area that compromise pre‐existing livelihoods both ecologically and via erosion of earlier protections on labour secured through the national oil workers union. The article thus argues for a conceptualisation of displacement induced by extractive industry that incorporates into its analysis the effects of industrial restructuring and expansion on extant production relations, in both the short and longer term.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.006
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.035
GPT teacher head0.205
Teacher spread0.170 · 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

Citations9
Published2015
Admission routes2
Has abstractyes

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