MétaCan
Menu
Back to cohort
Record W3201476986

States, Employers, and Gender Equality

2021· dissertation· en· W3201476986 on OpenAlex
Audrey Shannon Latura

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2021
Typedissertation
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGender equalityPolitical scienceGender studiesSociologyLabour economicsEconomics
DOInot available

Abstract

fetched live from OpenAlex

How do states impact whether employers provide work-family benefits like childcare and paid family leave, especially in national contexts of low social policy spending? What out- comes for women’s professional advancement and gender equality more broadly should we expect from these interventions? And what does public opinion tell us about what people think employers ought to be doing privately that the state is not? I explore these questions in this three-paper dissertation. In Chapter 1, I begin by looking at on-site childcare benefits provided privately by em- ployers in the liberal welfare states of Canada and the United Sates, two countries without universal, publicly-available childcare. Using an original panel dataset of high-revenue Cana- dian and US companies, I use a difference-in-differences design to show that state childcare regulation in the United States and provincial subsidies in Canada that include employers, especially in the province of Quebec, increase the supply of on-site childcare. I then deploy a field experiment to show how greater provision of on-site childcare results in greater female demand for the benefit and, in turn, greater professional advancement. In Chapter 2, a paper co-authored with Ana Catalano Weeks, we look at how corporate board gender quotas produce feedback effects on company policies that lead to greater gen- der equality. With a difference-in-differences approach, we use an original panel dataset of corporate reports from Italy, where a board quota was instituted, to Greece, where one was not. We look at changes in company programs and policies beyond the board, especially in the areas of women’s leadership throughout the company, childcare, paid leave, and schedul- ing flexibility. Qualitative analysis helps understand the context in which companies make iii these changes to their internal policies. Finally, in Chapter 3, I look at political preferences for work-family benefits provided by employers rather than the government. I use two case studies – the first with com- parative survey data and the second with an original survey of veterans who have used employer-provided childcare through the US Department of Defense – to understand how organizational and individual experience with employer benefits shapes preference for them. Qualitative interviews with veterans shed light on some of the potential mechanisms behind these pathways. In each chapter, I discuss the political and policy implications of these findings, especially for women, who are the main of childcare and paid family leave as the primary caretakers of children.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.072
GPT teacher head0.344
Teacher spread0.272 · 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