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Record W3157198132 · doi:10.1177/00208817211004026

A Crisis is a Terrible Thing to Waste: Feminist Reflections on the EU’s Crisis Responses

2021· article· en· W3157198132 on OpenAlexafffund
Heather MacRae, Roberta Guerrina, Annick Masselot

Bibliographic record

VenueInternational Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaEuropean Commission
KeywordsEuropean unionBrexitCrisis managementPolitical sciencePolitical economyNegotiationState (computer science)Face (sociological concept)Development economicsEconomic systemEconomicsSociologyInternational tradeLawSocial science

Abstract

fetched live from OpenAlex

As critics are quick to point out, the European Union (EU) has entered the crisis phase of its evolution. It could be argued that crisis management is now the EU’s new normal. Dealing with both endogenous (e.g., economic crisis and Brexit) and exogenous crises (e.g., the migrant crisis and COVID-19), the EU is facing a whole new set of challenges that has the potential to destabilize the complex institutional balance that has maintained the process of European integration over the last 70 years. In this environment of rapid responses, gender+ equality has frequently been compromised. As we argue in this article, the implications of this backsliding are grave not only for equality but also for the European Union as a whole. Drawing on Walby’s concept of gender regimes and social transformation, we consider current crises and the EU’s responses to those crises to highlight potentially dangerous shifts in the European gender regime. With crisis response increasingly supporting a neo-liberal gender regime, the current state of perpetual crisis in the European institutions does not bode well for the future of equality.

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)0.009
metaresearch head score (Gemma)0.007
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: Commentary · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.033
Scholarly communication0.0110.010
Open science0.0010.007
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0050.000

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 head0.236
GPT teacher head0.494
Teacher spread0.258 · 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
GenreCommentary

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
Published2021
Admission routes2
Has abstractyes

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