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Record W4320910711 · doi:10.7202/1096258ar

A healing curve: The poetry of Taqralik Partridge in Inuktitut translation

2023· article· en· W4320910711 on OpenAlexaffvenueabout
Valerie Henitiuk, Marc-Antoine Mahieu

Bibliographic record

VenueMeta Journal des traducteurs · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsConcordia University of Edmonton
Fundersnot available
KeywordsPoetryLiteratureColonialismPerspective (graphical)HistorySpoken wordReading (process)ArtLinguisticsVisual artsPhilosophyArchaeology

Abstract

fetched live from OpenAlex

Curved against the hull of a peterhead (PS Guelph 2020), a slender volume of 19 poems that “wrestle with colonialism and racial violence while also reflecting a rich sensory imagery” (Partridge 2020a) was released in January 2020. By May of that year, this first book by prize-winning short-story writer, artist and spoken word poet Taqralik Partridge already figured in a list of “six Inuit literature greats” deemed essential reading. Although Partridge composed all of these poems in English, three translated versions are provided alongside their originals in curved against. The present article focuses on the two poems accompanied by Inuktitut versions, translated by Ida Saunders and Looee Arreak respectively, with a view to engaging with Partridge’s work from the perspective of eco-translation. The language related to nature – how it is employed and especially how it is translated – proves relevant to the discussion, as does the act of translation, which highlights the inter-relatedness critical to survival, literally and metaphorically speaking, for Inuit and non-Inuit alike.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.007
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.002

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 head0.175
GPT teacher head0.325
Teacher spread0.150 · 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 designQualitative
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

Citations1
Published2023
Admission routes3
Has abstractyes

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