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Record W2024083022 · doi:10.7202/1028658ar

Dialogue, Reassurance and Understanding: Framing Political Translations during the 1980 and 1995 Quebec Sovereignty Referendums

2015· article· en· W2024083022 on OpenAlexaffvenueabout
Julie McDonough Dolmaya

Bibliographic record

VenueMeta Journal des traducteurs · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsYork University
Fundersnot available
KeywordsFrenchPoliticsFraming (construction)SovereigntyNationalismPolitical scienceMedia studiesSociologyHistoryLaw

Abstract

fetched live from OpenAlex

In Canada during the 1970s, 80s, and 90s, more than one thousand works – and about one hundred translations – were published on the topics of Quebec nationalism, independence movements, and sovereignty referendums, in both of Canada’s official languages. Despite the diversity of these publications, which included biographies, political analyses, and polemical essays, almost all the works touched on themes that have generated controversy in Canada. The paratexts in these translations are therefore an important resource that highlight perceived differences between the political opinions of Francophone and Anglophone readers. This article will analyze the paratexts in the English and French translations to show how the target language audience was encouraged to read a translation of a work that was very clearly not addressed to them, and which in some cases even criticized the very audience it now addressed. Finally, it will examine which features these English and French paratexts do and do not share, while trying to determine why these similarities and differences exist.

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)0.016
metaresearch head score (Gemma)0.029
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: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.831

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0410.041
Scholarly communication0.0170.006
Open science0.0020.006
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0050.000

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 head0.173
GPT teacher head0.287
Teacher spread0.113 · 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

Citations2
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueMeta Journal des traducteursSame topicTranslation Studies and PracticesFrench-language works237,207