MétaCan
Menu
Back to cohort
Record W4385867237 · doi:10.59962/9780774850421

Gendering Government

2007· book· en· W4385867237 on OpenAlexaboutno aff
Louise Chappell

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2007
Typebook
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Political scienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Feminists, like other political actors, cannot avoid the state. Whether they want equal pay, anti-domestic violence laws, refugee or childcare centres, they must engage with state institutions. What determines the nature and extent of this involvement? Why are some feminists more willing to engage with some institutions, while others are not? Gendering Government seeks to answer these questions through a comparison of feminist engagement with political institutions in Australia and Canada. Chappell considers what effect political institutions have had on shaping feminist claims, and in turn, to what extent these claims shape the nature of these institutions. She adds a new dimension to our understanding of the relationship between gender interests and government, showing how the interaction is dynamic and mutually defining. She further extends existing comparative studies in the field of women and politics by examining the full range of such institutions, including the electoral, parliamentary, legal/constitutional, and bureaucratic arenas.

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: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.013
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.003

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 head0.230
Teacher spread0.201 · 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
GenreOther

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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of British Columbia Press eBooksSame topicGender Politics and RepresentationFrench-language works237,207