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Record W2914115162 · doi:10.1177/1866802x1600800104

The Limits of Labor Legislation Reforms: Rigidity, Growth, and Employment in Brazil (1995–2010)

2016· article· en· W2914115162 on OpenAlexaff
Jean François Mayer

Bibliographic record

VenueJournal of Politics in Latin America · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsConcordia University
Fundersnot available
KeywordsEmployment protection legislationEconomicsLegislationLabour economicsSplit labor market theoryLabor relationsProsperityInformal sectorPovertyProductivityExplanatory powerEconomic inequalityInequalitySecondary labor marketMarket economyUnemploymentEconomic growthPolitical science

Abstract

fetched live from OpenAlex

The literature addressing market dynamics typically assumes that reforming labor legislation has a direct impact on economic performance, the configuration of labor markets, and the strength of labor organizations. Within this literature one prevalent school of thought advocates flexibilizing labor laws as the key to creating economic prosperity, enhancing labor productivity, increasing formal sector employment, and successfully fighting poverty and socioeconomic inequality. I test these assumptions by analyzing the case of Brazil between 1995 and 2010. My findings suggest that reforms seeking to flexibilize the Brazilian labor code do not significantly change the country's labor market or economy. I propose that transformations in international economic contexts as well as differing policy orientations of successive Brazilian federal governments may hold more explanatory power in accounting for labor market changes during this time period.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.306
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.332
Teacher spread0.305 · 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 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

Citations7
Published2016
Admission routes1
Has abstractyes

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