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Record W2954691347 · doi:10.1075/target.19093.nav

Translating from/for the margins of empire

2019· article· en· W2954691347 on OpenAlexaff
Aura Navarro, Catherine Poupeney Hart

Bibliographic record

VenueTarget International Journal of Translation Studies · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsUniversité de MontréalConcordia University
Fundersnot available
KeywordsCensorshipColonialismAudience measurementPerspective (graphical)Translation studiesPolitical scienceHistoryEmpirePosition (finance)Media studiesSociologyLawLiteratureArtEconomicsVisual arts

Abstract

fetched live from OpenAlex

Abstract The third series of the Gaceta de Guatemala (1797–1807) represents a high point of early journalistic production in colonial Spanish America. It benefitted from the presence of a particularly dynamic and cohesive group of young men involved in the development of the paper as a means of improving the social and economic situation of a territory extending from Chiapas to Costa Rica. Against a backdrop of censorship, and undeterred by their marginal position vis-à-vis the European centers of knowledge, they managed to include a surprising number of translations and references to foreign works. In conjunction with Colonial Studies, the Translation Studies perspective adopted in this article highlights how the editors of the Gaceta and their close collaborators, far from being passive consumers, managed to use translation as a tool to engage in, and prepare their readership for, dialogue with the Enlightened elites of the Western world.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0060.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.004

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 head0.127
GPT teacher head0.355
Teacher spread0.228 · 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 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

Citations15
Published2019
Admission routes1
Has abstractyes

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