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Record W4312572030 · doi:10.31857/s2686673022060025

Canada's Role in Shaping the Gender Agenda of Trade Agreements

2022· article· en· W4312572030 on OpenAlexaffabout
Olga I. Soldatenkova

Bibliographic record

VenueUSA & Canada Economics – Politics – Culture · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Human Rights and Reproductive Law
Canadian institutionsInstitute for Christian Studies
Fundersnot available
KeywordsNegotiationGender equalityInternational tradeCommercial policyPolitical scienceProcess (computing)International economicsBusinessEconomicsSociologyGender studies

Abstract

fetched live from OpenAlex

The recognition that trade policy is not gender-neutral and can have a different impact on men and women has caused an increase in attention to the gender aspects of trade agreements at all stages of the negotiation process. The article summarizes the main approaches used by the countries to include gender equality issues in trade agreements. Particular attention is paid to Canada's experience in this area. The conclusion is made about Canada’s leading role in shaping the gender agenda of trade policy and mechanisms for its implementation both at the national and international levels.

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)0.007
metaresearch head score (Gemma)0.011
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 score0.151
Threshold uncertainty score0.985

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0270.012
Scholarly communication0.0130.002
Open science0.0010.004
Research integrity0.0040.005
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 head0.034
GPT teacher head0.256
Teacher spread0.222 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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