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Record W2996547350 · doi:10.1017/aju.2019.74

Reimagining Trade Agreements for Workers: Lessons from the USMCA

2019· article· en· W2996547350 on OpenAlexaboutno aff
Álvaro Santos

Bibliographic record

VenueAJIL Unbound · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Labor and Employment Law
Canadian institutionsnot available
Fundersnot available
KeywordsGlobalizationCold warInternational tradeBacklashOrder (exchange)EconomicsCapital (architecture)Labour lawPower (physics)Trade barrierEconomic globalizationPolitical scienceInternational economicsLabour economicsMarket economyLawGeographyPolitics

Abstract

fetched live from OpenAlex

A backlash against the post-Cold War order of liberal globalization has taken hold in the rich North Atlantic countries. Concerns about wages, working conditions, and economic opportunity are central to the critique of international trade agreements of the last three decades. While labor rights have progressively been included in trade agreements, they have done little to reshape workers’ well-being and workplace conditions. The new United States-Mexico-Canada Agreement (USMCA) may signal a pivot to a new model requiring reforms of domestic labor law and other issues important to workers. However, there is much more to be done to rebalance the power between capital and labor in trade agreements. In addition, for the United States and other rich countries, reform at home may be equally important.

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)0.016
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.149
Threshold uncertainty score0.296

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0160.015
Scholarly communication0.0150.010
Open science0.0020.008
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0090.001

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 head0.059
GPT teacher head0.373
Teacher spread0.315 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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