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Record W2580993545 · doi:10.22140/pv.116

Engaging Women in Public Leadership in West Virginia

2016· article· en· W2580993545 on OpenAlexaboutno aff
Karen Kunz, Carrie M. Staton

Bibliographic record

VenuePublic Voices · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsAppalachiaLegislatureWest virginiaState (computer science)Quarter (Canadian coin)Inclusion (mineral)Executive summaryPopulationPublic administrationState legislaturePolitical scienceSociologyGender studiesLawGeographyDemographyArchaeologyBusiness

Abstract

fetched live from OpenAlex

As the 113th Congress begins to tackle the issues of the day, men and women alike celebrate the inclusion of a record number of women representatives. The historic numbers indicate progress, but the reality is that women compose slightly more than half of the national population but less than twenty percent of the national legislative representatives. Women fare slightly better at the state level, holding just under a quarter of state legislative seats and executive offices. In this study we explore the challenges faced and advances made by women in attaining statewide executive office in rural states by examining how they have fared in Appalachia and particularly West Virginia. We integrate theoretical understandings and statistical data with lived experiences gleaned from personal interviews conducted with the women who have held executive office in West Virginia.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.179
GPT teacher head0.331
Teacher spread0.152 · 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 designObservational
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

Citations1
Published2016
Admission routes1
Has abstractyes

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