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Record W3046710798

A CAPACIDADE ESTRATÉGICA DO TRANSPORTE MARÍTIMO DE CARGAS NO BRASIL: CENÁRIOS, AMEAÇAS E OPORTUNIDADES

2020· article· pt· W3046710798 on OpenAlexaboutno aff
Gabriela de Souza Agresta Hugo Silva, Isabela Sestelo de Britto, Ítalo de Araújo Wanderley Romeiro, Rafaela Vasconcelos Senra, Rodrigo Rendeo Silva Lima, Henrique Campos de Oliveira

Bibliographic record

VenueSeminário Estudantil de Produção Acadêmica · 2020
Typearticle
Languagept
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Almirante Mahan ja apontava que a projecao internacional de paises costeiros perpassa, necessariamente, pela capacidade estrategica desses estados sobre os fluxos do comercio internacional e do Transporte Maritimo de Cargas (TMC). Nesse sentido, frente a crescente atividade dos complexos logisticos internacionais portuarios, torna-se fundamental questionar: “Como a politica nacional pode contribuir, estrategicamente, com a melhor insercao internacional do Brasil via atividade maritima de cargas?” Assim, delineamos a seguinte metodologia, baseada na revisao bibliografica e coleta de dados quali quantitativos: tipificar as coalizoes e paradigmas no TMC; descrever o contexto atual da Marinha Mercante frente a politica nacional do TMC; realizar estudo comparado entre Brasil, EUA, China, Canada e Australia; e prospectar cenarios para acao. Identificou-se que a politica de TMC no Brasil e industrial nacional corporativa, ou seja, centralizada no governo federal e com baixa competitividade e insercao internacional. Ha forte tendencia ao paradigma industrial liberal. Estrategicamente, a politica nacional do TMC pode apoiar cenarios que favorecam a inclinacao para se tornar pos-industrial liberal ou pos-industrial nacional corporativa para melhor posicionamento internacional do pais.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.232
Teacher spread0.211 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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