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'Verás que um filho teu não foge à luta': histórias de emigrados brasileiros nas Forças Armadas dos EUA

2015· dissertation· pt· W2625862954 on OpenAlexfundno aff
Thomas Machado Monteiro

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldSocial Sciences
TopicMigration, Racism, and Human Rights
Canadian institutionsnot available
FundersUniversity of OxfordYork University
KeywordsPolitical science

Abstract

fetched live from OpenAlex

\n O presente trabalho tem como objetivo investigar e registrar a participação de brasileiros nas Forças Armadas dos EUA desde a Guerra do Vietnã até o presente momento. O fenômeno do alistamento militar de estrangeiros nas forças de batalha estadunidenses remonta aos tempos da Guerra de Secessão e compõe parte importante da história de diversas comunidades imigrantes no país. Desde a Guerra do Vietnã, há relatos de brasileiros lutando pelos EUA. No entanto, o fenômeno vira uma tendência mais numerosa a partir do momento que a imigração brasileira ganha maior expressão, na década de 1980. O trabalho busca, portanto, quantificar e discutir esta participação tanto a partir do ponto de vista da comunidade emigrada, quanto do ponto de vista individual dos emigrados entrevistados.\n

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), Science and technology studies, Research integrity, 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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.043
GPT teacher head0.350
Teacher spread0.307 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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