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Record W2566067104

NGO Translation and Translator Practices Explored Through an Ideological Lens

2014· dissertation· en· W2566067104 on OpenAlexaboutno aff
Maya-Lin Sylvia Worth

Bibliographic record

VenueYorkSpace (York University) · 2014
Typedissertation
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyFunctionalism (philosophy of mind)SociologyContext (archaeology)Plan (archaeology)Critical discourse analysisTranslation studiesPolitical scienceEpistemologyLinguisticsPoliticsLawPhilosophyHistory
DOInot available

Abstract

fetched live from OpenAlex

This thesis project looks at translation and translator practices in the world of Canadian development-NGOs. Given this context, both translation and development studies are drawn upon within this project. Focusing on the ideological aspects of these practices, theories of functionalism and critical discourse analysis (CDA), as they relate specifically to translation studies, are employed. After presenting this framework, two types of analyses follow, which allow us to interrogate the ideology of such NGO translation and translator practices. First, the specific translations found in the promotional videos drawn from one organization, Plan Canada, are presented and analyzed. Later, translators and their practices are investigated though empirical research and more general investigations of several different NGOs’ website content. Finally, how ideology is manifested in these practices is related to greater ideological tendencies within our global society.

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)0.017
metaresearch head score (Gemma)0.019
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 score0.105
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.007
Science and technology studies0.0180.035
Scholarly communication0.0150.008
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.122
GPT teacher head0.332
Teacher spread0.210 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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