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Record W2981104363 · doi:10.1111/imig.12640

Closing the Gap? Gender and the Global Compacts for Migration and Refugees

2019· article· en· W2981104363 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Migration · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsOperationalizationRefugeeNegotiationCivil societyClosing (real estate)Corporate governancePolitical scienceState (computer science)SociologyEconomic growthLawManagementEconomicsPolitics

Abstract

fetched live from OpenAlex

Abstract Migrant women's organizations, UN Women, and civil society advocacy networks have mobilized to call for greater gender‐responsiveness in migration governance. The development of the Global Compacts on Migration and Refugees presented an important opportunity to continue enhancing the international framework for protecting the rights of women and men on the move. This article asks: How has gender been understood/invoked during proceedings leading up to their adoption? In what ways is it incorporated in the resulting compacts and their operationalization? What are the gains and missed opportunities for gender‐responsiveness? Drawing on data gathered through participant observation in the global compact on migration preparatory meetings and member state negotiations in Geneva and New York, and policy analysis of the drafts of both compacts, this paper aims to determine the extent to which the compacts, and the plans to operationalize them, serve to widen or close the gender gap.

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: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.983

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 communication0.0000.001
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 head0.026
GPT teacher head0.335
Teacher spread0.309 · 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