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Record W1560603767 · doi:10.5860/choice.42-1034

Equity in the workplace: gendering workplace policy analysis

2004· article· en· W1560603767 on OpenAlexaboutno aff

Bibliographic record

VenueChoice Reviews Online · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)Labour economicsBusinessSociologyEconomicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Chapter 1 Preface Chapter 2 Introduction Part 3 Theoretical Perspectives on Gender and Workplace Policy Chapter 4 Globalization, Gender and Work: Perspectives on Global Regulation Chapter 5 Policy Strategies in a Global Era for Gendered Workplace Equity Chapter 6 Institutionally Embedded Gender Models: Re-regulating and Breadwinner Models in Germany and Japan Chapter 6 European Gender Mainstreaming: Promises and Pitfalls of Transformative Policy Part 7 Implications of Gender in the Workplace Chapter 9 Parental Leave and Gender Equality: What Can the U.S. Learn from the European Union? Chapter 9 Career Advancement Choices of Female Managers in U.S. Local Government Chapter 10 An Assessment of Women's Acceptance as Breadwinners Chapter 11 The Employment Insurance Model: Maternity, Paternal, and Sickness Benefits in Canada Part 11 Reconciliation of Work and Family Life: Maternity, Parental, and Family Leave Chapter 12 Erosion of the Male-Breadwinner Model? Female Labor-Market Participation and Family-Leave Policies in Germany Chapter 13 Solving a Problem or Tinkering at the Margins? Work, Family and Caregiving Chapter 13 Globalization and Work/Life Balance: Gendered Implications of New Initiatives at a U.S. Multinational in Japan Chapter 14 Europeanizing the Military: The ECJ as a Catalyst in the Transformation of the Bundeswehr Part 17 Specific Applications of Workplace Policies: Gender in Equity in the Workplace Chapter 19 Implementing Sexual Harassment Law in the United States and Germany Chapter 20 Sexual Harassment Policies and Employee Preferences in Local U.S. Government

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.091
GPT teacher head0.444
Teacher spread0.353 · 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 designNot applicable
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

Citations14
Published2004
Admission routes1
Has abstractyes

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