MétaCan
Menu
Back to cohort
Record W2888149020 · doi:10.1093/pa/gsy032

Political Staff and the Gendered Division of Political Labour in Canada

2018· article· en· W2888149020 on OpenAlexaboutno aff
Feodor Snagovsky, Matthew Kerby

Bibliographic record

VenueParliamentary Affairs · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsLegislaturePoliticsHouse of CommonsParliamentWork (physics)Variety (cybernetics)Political sciencePublic administrationSociologyDivision of labourAffect (linguistics)Political economyLaw

Abstract

fetched live from OpenAlex

Abstract While there is considerable research on elected legislators in a variety of contexts, the academic knowledge about their advisors is very limited. This is surprising, given a considerable portion of work attributed to legislators is performed by political staff. Further, political advising increasingly serves as a training ground for future politicians in many professionalised legislatures. We use a mixed-methods approach to understand how the influence of men and women differs in political advising positions in the case of Canada’s House of Commons, and how this may affect women’s political ambition. We demonstrate while close to an equal number of men and women work for MPs in a political capacity on Parliament Hill, men continue to dominate legislative roles while women continue to dominate administrative roles. Further, legislative work increases political ambition, which means more men benefit from the socialising effects of legislative work than 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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.863

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0210.007
Scholarly communication0.0050.001
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.019
GPT teacher head0.288
Teacher spread0.269 · 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 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueParliamentary AffairsSame topicGender Politics and RepresentationFrench-language works237,207