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Record W4385588228 · doi:10.5040/9781501394140

Language Smugglers

2023· book· en· W4385588228 on OpenAlexaboutno aff
Arianne Des Rochers

Bibliographic record

VenueBloomsbury Publishing Plc eBooks · 2023
Typebook
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousMulticulturalismLinguisticsPoliticsImmigrationMinority languageQueerSociologyPolitical scienceGender studiesPhilosophyLaw

Abstract

fetched live from OpenAlex

Translation is commonly understood as the rendering of a text from one language to another – a border-crossing activity, where the border is a linguistic one. But what if the text one is translating is not written in “one language;” indeed, what if no text is ever written in a single language? In recent years, many books of fiction and poetry published in so-called Canada, especially by queer, racialized and Indigenous writers, have challenged the structural notions of linguistic autonomy and singularity that underlie not only the formation of the nation-state, but the bulk of Western translation theory and the field of comparative literature. Language Smugglers argues that the postnational cartographies of language found in minoritized Canadian literary works force a radical redefinition of the activity of translation altogether. Canada is revealed as an especially rich site for this study, with its official bilingualism and multiculturalism policies, its robust translation industry and practitioners, and the strong challenges to its national narratives and accompanying language politics presented by Indigenous people, the province of Québec, and high levels of immigration.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.553
Threshold uncertainty score0.899

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0160.006
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0310.007

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 head0.063
GPT teacher head0.258
Teacher spread0.195 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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