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Record W4319736349 · doi:10.17645/pag.v11i1.6174

Trade Policy and Ecological Transition

2023· article· en· W4319736349 on OpenAlexaff
Mathieu Dufour

Bibliographic record

VenuePolitics and Governance · 2023
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsMultinational corporationProfitability indexInvestment (military)CommodityEconomicsOrder (exchange)Economic systemBusinessMarket economyEcologyInternational economicsPolitical sciencePolitics

Abstract

fetched live from OpenAlex

While the global pandemic has taken the front stage since the spring of 2020, environmental issues remain as pressing as ever. In this article, I question whether the current liberalized trade and investment regime is consistent with the possibility of an ecological transition and argue that it is not. The organization of a large part of economic activity on a world scale by multinational corporations, with profitability imperatives and relatively short planning horizons, is inherently conducive to an intensification of resource extraction and commodity production. A liberal trade and investment regime gives free rein to these dynamics, which should instead be curtailed in order to achieve the necessary adjustments to sustainable living. As such, this article will explore ways in which the trade and investment regime could be subordinated to ecological and social concerns and contribute to, rather than hinder, an ecological transition.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0070.004
Open science0.0000.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.212
Teacher spread0.202 · 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 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

Citations6
Published2023
Admission routes1
Has abstractyes

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