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Record W4392526425 · doi:10.38116/ppe50n3art4

Vou de táxi? Uma análise da oferta de trabalho de motoristas de táxi no Brasil

2022· article· pt· W4392526425 on OpenAlexaff
Cristiano Aguiar de Oliveira, Gabriel Costeira Machado

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsTransport Canada
Fundersnot available
KeywordsPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Este artigo, as horas trabalhadas e os salários dos motoristas de táxi brasileiros são utilizados para testar duas teorias concorrentes a respeito da oferta de trabalho: a teoria neoclássica, que prevê elasticidades positivas; e a teoria dos rendimentos de referência, que prevê elasticidades negativas. Para este fim, utilizam-se informações da PNAD Contínua para estimar modelos com dados de corte e dados em painel para o período compreendido entre o primeiro trimestre de 2012 e o primeiro trimestre de 2014. São estimados modelos por mínimos quadrados ordinários, por mínimos quadrados em dois estágios e pelo método dos momentos generalizados. Os resultados indicam elasticidades negativas que podem implicar que os motoristas brasileiros utilizam algum rendimento de referência nas suas decisões de ofertar trabalho. Ademais, estes mostram que os motoristas possuem uma curva de aprendizado com a experiência que permite prever os seus rendimentos e realizar uma escolha melhor da sua quantidade de horas trabalhadas. O artigo conclui que este comportamento, associado à legislação vigente, pode gerar um racionamento na oferta do serviço de transporte urbano de passageiros.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0730.001

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 head0.010
GPT teacher head0.247
Teacher spread0.237 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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