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Record W4283168091 · doi:10.1111/1468-0424.12618

A Messy Mix: Religion, Feminism and Pentecostals

2022· article· en· W4283168091 on OpenAlexaffabout
Linda M. Ambrose

Bibliographic record

VenueGender & History · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsLaurentian University
Fundersnot available
KeywordsFeminismSecularismSociologyGender studiesReligiosityPoliticsLawPolitical science

Abstract

fetched live from OpenAlex

Abstract Scholars of Canadian history have been remiss in overlooking conservative religious women, especially when such women claimed to be feminists. Given the commonly shared assumption that second‐wave feminism was tied to secularism, the idea that religious women could be committed feminists seems implausible. However, some conservative Christian women, including evangelicals and Pentecostals, considered themselves to be feminists, even as they actively opposed abortion. The Rev. Bernice Gerard (1923–2008) was a Pentecostal pastor, a media personality and a municipal politician in Vancouver from 1977 to 1980. Researching her life through using her own life writing provides a case study for grappling with larger questions about conservativism and feminism. In 2000, Gerard, the self‐proclaimed feminist, was named as the most significant spiritual figure in British Columbia in the twentieth century. My biographical work about her pays particular attention to her provocative and seemingly contradictory convictions and points to how she resolved the conceptual tensions that framed her religiosity using a process of ‘self‐authoring’. Theoretical frameworks from the sociology of religion challenge Western feminism's implicit biases and provide useful ways to frame the complexities and paradoxes that arise in the lives of conservative women.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.085
Threshold uncertainty score0.619

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0260.025
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.029
GPT teacher head0.231
Teacher spread0.202 · 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
Published2022
Admission routes2
Has abstractyes

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