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Record W4285551790 · doi:10.7202/1088354ar

The consecration of languages through translation awards in Sweden (1970–2015)

2021· article· fr· W4285551790 on OpenAlexvenueno aff
Alva Dahl, Elin Svahn

Bibliographic record

VenueMeta Journal des traducteurs · 2021
Typearticle
Languagefr
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingDominance (genetics)Translation studiesHierarchyLinguisticsCapital (architecture)SociologyHistoryPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

This paper examines the role of translation awards in strengthening the literary capital of source languages. Focusing on three Swedish translation awards between 1970 and 2015, and comparing the awarded source languages to 1) the most central and influential literary languages in world literature and 2) Swedish publishing statistics 1970–2015, the aim is to position translation awards as an area of research within Translation Studies, as well as to investigate translation awards as a means of consecrating source languages in the target culture. Furthermore, we ask how these translation awards transfer different forms of symbolic capital back to the awarding institutions. The results from the comparisons show both similarities and differences, indicating that in the Swedish literary field, there are slight variations to the general global hierarchy of languages. The awarding patterns from the three translation awards studied are also in line with the profiles of the different awarding institutions. As could be expected, English is the most awarded language, although its dominance is strikingly small when compared to publishing statistics. This indicates that the literary capital of English is not unlimited; semi-central or even peripheral languages can transfer other sorts of values to the awarding institutions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.116
GPT teacher head0.346
Teacher spread0.230 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2021
Admission routes1
Has abstractyes

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