Las traducciones como fuentes para la prensa en el siglo XIX: el caso de la Gaceta de Caracas
Bibliographic record
Abstract
This article studies the influence of translations published in the Gaceta de Caracas during the Independence and the First Republic of Venezuela. The study consisted of three stages: 1) identification of translations; 2) comparative analysis between source texts (STs) and target texts (TTs); and 3) analysis of translation strategies. As a result, English is the most translated language in the gazette, given that the majority of source texts were taken from American and British newspapers. The content of the translations is largely political; all translations are anonymous. We observed the use of summary and periphrasis; literal translation was also a frequently used translation technique. Notably, appropriation was utilized as a translation strategy in half of the translations. To sum up, translation in the Gaceta de Caracas contributed to the consolidation of Venezuelan independence and the creation of the First Republic of Venezuela due to the use of appropriation combined with the political purposes of the translators. Received: 06-09-09 /Accepted: 19-11-09 How to reference this article: Navarro, A. (2010) Las traducciones como fuentes para la prensa en el siglo XIX: el caso de la Gaceta de Caracas. Íkala 15(1), pp.15-43.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".