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Record W4400446128 · doi:10.1086/729830

Gender and Political Economy: Revisiting Distributive Analysis

2024· article· en· W4400446128 on OpenAlexaff
Libby Adler, Deborah Dinner, Kerry Rittich, Nicole Štýbnarová, Chantal Thomas, Yiran Zhang

Bibliographic record

VenueSigns · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsWomen's and Gender Studies et Recherches Féministes
Fundersnot available
KeywordsPoliticsDistributive propertyPolitical scienceEconomic systemPolitical economyEconomics

Abstract

fetched live from OpenAlex

This roundtable brings together a group of legal scholars whose projects concern gender and political economy. These speakers, drawing from critical legal thought (including American legal realist and post-realist traditions), sociological and historical analyses of social reproduction, critical race theory and racial capitalism, postcolonial history and theory, and feminism and queer theory, discuss methods for assessing legal rules and architectures as distributional mechanisms that affect social groups defined by gender, race, class, and sexuality. While liberal ideology imagines law as an external regulatory force, the coauthors understand law to constitute economies, families, corporations, and other institutions of governance. They discuss the utility of critical and genealogical methods to excavate law’s allocation of burdens and benefits to different social groups positioned in the market, the state, the global economy, and the family.

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)0.010
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0050.034
Scholarly communication0.0100.017
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.050
GPT teacher head0.375
Teacher spread0.326 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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