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Record W2148624710 · doi:10.1177/0042098014528392

Gender and commuting time in São Paulo Metropolitan Region

2014· article· en· W2148624710 on OpenAlexaff
Raul da Mota Silveira Neto, Gisléia Benini Duarte, Antonio Páez

Bibliographic record

VenueUrban Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMicrodata (statistics)Metropolitan areaMarital statusCensusDemographic economicsEmpirical researchGeographySociologyDemographySocioeconomicsPopulationEconomics

Abstract

fetched live from OpenAlex

Gender differentials in commuting have been reported in the literature, often couched within the household responsibility hypothesis. This hypothesis attributes shorter commutes to females due to a disproportionate load of household responsibilities. The objective of the present study is to report research regarding commuting time in São Paulo Metropolitan Region, in Brazil. Based on microdata from the Demographic Census of 2010 the focus of the present study is on the role of marital status and presence of dependents on gender differentials in commuting time. Specifically, the research seeks to determine whether there is empirical support in this region for the household responsibility hypothesis. The results suggest that marital status exerts a stronger influence on the commuting time of working women, with the number of dependents (children and elderly) exerting a smaller influence on commuting time. Gender differentials are observed also for single and formerly married working females, which suggests other cultural or environmental factors not fully captured by the household responsibility hypothesis. Most studies, however, are set in North America. This research contributes towards the development of a broader, international knowledge foundation regarding gender and commuting patterns.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.078
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.063
GPT teacher head0.333
Teacher spread0.270 · 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

Citations75
Published2014
Admission routes1
Has abstractyes

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