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Record W4409099031 · doi:10.3138/chr-2024-0058

Feminists Confront the Neoliberal Turn: The Third United Nations World Conference on Women, Nairobi, 1985

2025· article· en· W4409099031 on OpenAlexaffvenueabout
Amanda Ricci

Bibliographic record

VenueCanadian Historical Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsYork University
Fundersnot available
KeywordsPolitical scienceEconomic growthGender studiesDevelopment economicsPolitical economyEconomic historySociologyHistoryEconomics

Abstract

fetched live from OpenAlex

Held in Mexico City (1975), Copenhagen (1980), and Nairobi (1985), the United Nations (UN) World Conferences on Women attracted women from all over the world for two concurrent events. National governments and UN-recognized national liberation movements participated in the first meeting, a formal encounter where delegations voted on UN policy documents. Steeped in protocol, the official meetings stood in sharp contrast to the second event, the Forum, a cacophony of grassroots organizers and non-governmental organizations. The Forums allowed participants to speak beyond their official delegations as well as to make the type of connections that would further internationalize women’s movements. This article examines Canada’s role at the third conference – the World Conference to Review and Appraise the Achievements of the United Nations Decade for Women – which was held in Nairobi, Kenya. Against a backdrop of intensifying neoliberalism, grassroots organizers, national liberation movements such as the African National Congress (ANC) and the Palestinian Liberation Organization (PLO), and national governments engaged in contentious debates over the meaning of women’s rights. Focused on the 1980s, the article argues that genuine political alternatives existed in Canada and internationally alongside a turn to conservative thinking.

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)0.004
metaresearch head score (Gemma)0.003
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 score0.894
Threshold uncertainty score0.497

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0140.009
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.076
GPT teacher head0.328
Teacher spread0.251 · 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
Published2025
Admission routes3
Has abstractyes

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