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Record W4315700672 · doi:10.1177/00219096221144686

Pathways to Politics for Women Parliamentarians in Myanmar

2023· article· en· W4315700672 on OpenAlexafffund
Philippe Doneys, Kyoko Kusakabe, Joyee S. Chatterjee, Soe Myat Tun, Khin Cho Myint, Franque Grimard

Bibliographic record

VenueJournal of Asian and African Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsMcGill University
FundersInternational Development Research Centre
KeywordsParliamentDemocratizationPoliticsPolitical scienceSocializationFace (sociological concept)Gender studiesPolitical economyPublic relationsSociologyDemocracyLawSocial science

Abstract

fetched live from OpenAlex

The number of women parliamentarians in Myanmar increased during the last decade of democratization before the February 2021 coup d’état yet remained extremely low at about 15% of parliament in the 2020 election. This paper uses the concept of political pathway to explore barriers and opportunities that women parliamentarians experienced along their life course. It does so through in-depth interviews conducted in early 2020 with 20 women and 10 men parliamentarians elected in the 2015 general election. Results suggest that women tend to take distinct pathways from men and face specific opportunities and barriers through supply-driven factors such as parental socialization, experience of national crises, available peer networks, acquired professional experiences, and available family support, and through a main demand-driven factor in party recruitment and politics. This informs recommendations in the conclusion in terms of increasing resources and support available to women and addressing discrimination by political parties.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

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 studies0.0090.002
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.060
GPT teacher head0.351
Teacher spread0.291 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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