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Record W3043045256 · doi:10.1080/07491409.2020.1781315

Gender Equality through a Neoliberal Lens: A Discourse Analysis of Justin Trudeau’s Official Speeches

2020· article· en· W3043045256 on OpenAlexaffabout
Pascale Dangoisse, Gabriela Perdomo

Bibliographic record

VenueWomen s Studies in Communication · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFeminismNeoliberalism (international relations)ProsperityGender studiesPoliticsSociologyPrime ministerPolitical scienceGender equalityPolitical economyLaw

Abstract

fetched live from OpenAlex

Justin Trudeau, the current prime minister of Canada, says he is a feminist. His government has formulated a feminist foreign policy and has presented official budgets alluding to intersectional feminism. Through discourse analysis, we examine how Trudeau’s self-description as a feminist manifests in his official speeches spanning from 2015 to 2018; we also situate his positioning in relation to contemporary literature on intersectional feminism. Our study illustrates what other scholars have identified as an increasingly difficult relationship between feminism and the dominant discourse of neoliberalism in political and policy circles. Our findings suggest that Prime Minister Trudeau’s understanding of feminism appears contained within and limited by a discourse of economic prosperity, which puts his positioning in line with a form of neoliberal feminism. We conclude that, in the analyzed speeches, the prime minister frames matters of gender equality primarily as a means to unleash women’s potential to contribute to economic prosperity, portraying them as an untapped resource.

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 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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.229
GPT teacher head0.409
Teacher spread0.180 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations12
Published2020
Admission routes2
Has abstractyes

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