MétaCan
Menu
Back to cohort
Record W1990154071 · doi:10.7202/031011ar

“Il en faut un peu”: Farm Women and Feminism in Québec and France Since 1945

2006· article· en· W1990154071 on OpenAlexvenueaboutno aff
Gail Cuthbert Brandt, Naomi Black

Bibliographic record

VenueJournal of the Canadian Historical Association · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsFeminismGender studiesPoliticsSociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Certain farm women's organizations continue to represent the social feminist tradition of Canadian suffragism and the broader social Catholic feminism still influential elsewhere. Canadian historians have often criticized such groups in contrast with a more aggressive, equal-rights feminism found among urban and rural women in both waves of feminism. We argue that, far from being conservative, groups identified as social feminist serve to integrate farm women into public debates and political action, including feminism. We outline the history of the Cercles de fermières of Québec, founded in 1915, and the French Groupements de vulgarisation-développement agricoles féminins, founded since 1959. A comparison of members with nonmembers in each country and across the group, based on survey data collected in 1989 for 389 cases, suggests that club involvement has counteracted demographic characteristics expected to produce antifeminism. In general, we find less hostility to second-wave feminism than might be expected. Relying mainly on responses to open-ended questions, we argue that, for our subjects, feminism is tempered by distaste for confrontation. Issues supported by the movement for women's liberation are favoured by farm women, but the liberationist style and tactics are eschewed. Those of our respondents identified as feminists express preference for a complementarity modelled on the idealized family.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.004
GPT teacher head0.179
Teacher spread0.175 · 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 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

Citations6
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Historical AssociationSame topicCanadian Identity and HistoryFrench-language works237,207