MétaCan
Menu
Back to cohort
Record W2166761864 · doi:10.7202/009381ar

Breve historia de la secretaría de interpretación de lenguas

2004· article· en· W2166761864 on OpenAlexvenueno aff
Ingrid Cáceres Würsig

Bibliographic record

VenueMeta Journal des traducteurs · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Linguistics and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesState (computer science)Political scienceService (business)HistoryLinguisticsArtPhilosophyBusinessComputer science

Abstract

fetched live from OpenAlex

The article traces the history of the Secretaría de Interpretación de Lenguas (Language Interpreting Secretariat), which was created by Charles V in 1527 to support the Consejo de Estado (Council of State) and which can be considered as a pioneering organization in Europe in the field of “official” translation. Here we can find also the origin of the sworn translation in the Iberian Peninsula. At the same time and from the 18th century so-called traductores de Estado (State translators) started to work directly for other state offices, whose activity is also described. At the end of the 18th century a new figure emerges, namely the joven de lenguas (jeunes de langues), which can be considered as the first step in the development of the diplomatic career. More specifically, the following main questions will be answered: When and why was an official translation and interpreting service first created in Spain? What was its incumbent? Who worked for this service and how did applicants enter the office? Which languages and what type of documents were translated? How were these linguistic services remunerated?

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)0.006
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0050.023
Scholarly communication0.0130.007
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.025
GPT teacher head0.257
Teacher spread0.232 · 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
GenreOther

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

Citations14
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueMeta Journal des traducteursSame topicHistorical Linguistics and Language StudiesFrench-language works237,207