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Record W2469628251 · doi:10.52034/lanstts.v2i.90

Traduire pour transmettre: le cas des textes amérindiens.

2021· article· en· W2469628251 on OpenAlex
Danielle Cyr, Alexandre Sévigny

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLinguistica Antverpiensia New Series – Themes in Translation Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsMcMaster UniversityYork University
Fundersnot available
KeywordsLinguisticsContext (archaeology)Section (typography)HistoryHumanitiesComputer sciencePhilosophyArchaeology

Abstract

fetched live from OpenAlex

This article explores two sorts of problems that postcolonial amerindian translation poses: grammatical facts and socio-cultural context. In a first section, we discuss specific grammatical facts occurring in some First Nations languages that pose difficulties to the translator. In a second section, we discuss the process of translation of amerindian texts, concentrating on who is doing the translating and the importance of translation to the survival of endangered amerindian languages. All discussion is framed by the fact that amerindian languages are currently situated in amerindian cultures which are the product of colonial influences that shaped the socio-historical context within which amerindian languages evolved. These problems are discussed with specific reference to Mìgmaq, Innu and Montagnais, all endangered amerindian languages spoken in Canada and the United States. The target languages for the translations are either French or English.

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.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.569
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.100
GPT teacher head0.398
Teacher spread0.298 · 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