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Record W4405059560 · doi:10.22456/2178-8839.136340

A China e a armadilha da dívida

2024· article· pt· W4405059560 on OpenAlex
Diego Pautasso, Isis Paris Maia

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConjuntura Austral · 2024
Typearticle
Languagept
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsCanadian Medical Protective Association
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

A armadilha da dívida (debt trap), conceito criado por Brahma Chellaney, atribuiu à China a responsabilidade por financiar grandes projetos de infraestruturas em países periféricos e depois, em função do endividamento, estabelecer um ciclo vicioso de dependência. Metodologicamente, buscamos as palavras “China debt trap” em quatro veículos de mídia estadunidense - Washington Post, New York Times, CNN e Associated Press - e confrontamos com uma revisão de literatura no portal CAPES-Cafe sobre a temática. Trata-se de compreender a narrativa difundida pelo poder multimidiático estadunidense para localizar suas origens e contradições. Essa abordagem comparativa contribuiu para elucidar como os Estados Unidos mobilizam o poder multimidiático para que esse léxico e gramática subsidie suas doutrinas e política internacional. Nesse sentido, o principal achado é a genealogia por detrás do conceito (Armadilha da dívida) e como este é parte do conjunto de políticas antichinesas voltadas a interditar a ascensão da China num quadro de transição sistêmica.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.004

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 head0.048
GPT teacher head0.353
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