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Record W4308201664 · doi:10.18357/tar131202220789

Allied Interpreters: Exploring the Role Perception and Ethics of Uncertified Interpreters Supporting Migrant Agricultural Workers in British Columbia

2022· article· en· W4308201664 on OpenAlexaffvenueabout
Arista Marthyman

Bibliographic record

VenueThe Arbutus Review · 2022
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsInterpreterPerceptionWork (physics)Migrant workersStyle (visual arts)Interpretation (philosophy)Public relationsLanguage barrierPolitical sciencePsychologySocial psychologyEconomic growthLawGeographyLinguisticsEconomics

Abstract

fetched live from OpenAlex

Uncertified interpreters enable migrant agricultural workers in Canada’s Seasonal Agricultural Worker Program to access key resources and connect with community. Through providing a range of services, including support work and advocacy, interpreters assist migrant workers at risk of exploitation and injury in Canada. This article explores how uncertified interpreters navigate the power dynamics between migrant workers, interpreters, and other actors. Moreover, this article investigates how uncertified interpreters perceive their role and the ethical values that guide their communicative methods. This study’s research findings show that interpreters may adopt a pro-worker role perception as they gain knowledge of the disempowerment experienced by migrant workers. Arising from this role perception, interpreters may also adopt pro-worker ethical values that renounce interpreter neutrality in favour of accessibility and an explanatory communication style. Ultimately, this article contends that uncertified interpreters may reject some traditional interpretation guidelines to adopt a role perception, ethical framework, and communicative style perceived to be more well-suited to supporting migrant farm workers in British Columbia.

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 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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.109
GPT teacher head0.404
Teacher spread0.296 · 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 teacher head, not a consensus.

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
Published2022
Admission routes3
Has abstractyes

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