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Caminhos de ferro e desenvolvimento econômico na Índia e em Portugal: uma comparação entre as linhas de Mormugão e do Tua, c. 1880 - c. 1930 e adiante

2019· article· pt· W2964686048 on OpenAlexaff
Hugo Silveira Pereira, Ian J. Kerr

Bibliographic record

VenueRevista Brasileira de História · 2019
Typearticle
Languagept
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHumanitiesArtPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Resumo No final do século XIX, Portugal empreendeu a construção de dois caminhos de ferro de bitola reduzida na província continental de Trás-os-Montes e no domínio colonial de Goa, na Índia, dois territórios subdesenvolvidos sob soberania portuguesa. Ambos eram aplicações práticas do programa português de grandes obras públicas, conhecido historicamente como Fontismo, o qual propunha a angariação de capital nos mercados internacionais e sua aplicação na melhoria do sistema de transportes nacional, antecipando o desenvolvimento econômico das regiões atravessadas pela ferrovia e a criação de suficiente atividade econômica para pagar os empréstimos. Neste artigo, realiza-se um exercício de comparação histórica usando a metodologia do comparativismo, sugerida por Michel Espagne. Realçam-se as diferenças e semelhanças entre as duas linhas férreas, tanto durante o processo de decisão, como durante a operação. Demonstra-se como projetos similares tiveram resultados diferentes, de acordo com as circunstâncias correntes, mas também como estes resultados variam conforme o tempo histórico no qual são analisados. Espera-se contribuir para o debate sobre as fricções entre generalidades e especificidades no processo histórico.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient 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 score0.322
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.014

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 head0.020
GPT teacher head0.242
Teacher spread0.223 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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