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Record W2823403479 · doi:10.22456/2176-5456.56430

ANÁLISE DA POSSIBILIDADE DE RIVALIDADE NO MERCADO BANCÁRIO BRASILEIRO ENTRE 2000-2012

2018· article· pt· W2823403479 on OpenAlexaff
Mariana Araújo e Silva Bottrel, Mariusa Momenti Pitelli, Adelson Martins Figueiredo

Bibliographic record

VenueAnálise Econômica · 2018
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

A crise financeira mundial de 2008 alterou a arquitetura do setor bancário brasileiro através de grandes fusões e aquisições, que proporcionaram um aumento da concentração. Essa mudança causa preocupação sobre os níveis de concorrência do setor. A metodologia abordada envolve a análise da parcela de mercado apropriada pelos cinco maiores bancos no período e a sua oscilação. Associa, portanto, através de testes de raiz unitária, a instabilidade das séries temporais de market shares à possibilidade de rivalidade e de exercício de poder de mercado. Pode-se dizer que para o mercado de depósito total existe possível rivalidade para os bancos estudados, o que reduz a possibilidade do exercício de poder de mercado devido a um aumento da concentração.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.321
Threshold uncertainty score0.639

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.064
GPT teacher head0.339
Teacher spread0.276 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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