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Record W7043136654

Signed Language Interpreter Education Programs in North America: A Descriptive Study

2024· article· en· W7043136654 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of North Florida Digital Commons (University of North Florida) · 2024
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationInterpreterCurriculumDescriptive researchDescriptive statisticsWork (physics)Data collectionHigher educationUSableCurriculum development
DOInot available

Abstract

fetched live from OpenAlex

The objective of this study is to provide interpreter education faculty, university administrators, accrediting bodies, stakeholders, interpreters, and students (current or prospective) a descriptive snapshot-in-time of interpreter education curriculum and programs in North America. This study expands upon work done in the late 1987-1990 and 2007-2009 to capture a descriptive snapshot-in-time of the preparation of signed language interpreters. Researchers anticipated learning how programs align their curricula with CCIE accreditation standards (whether they are accredited or not), how two- and four-year programs (including Canada) allocate faculty time and resources, and how student characteristics and support systems differ among programs. This study examined interpreting education programs (IEP) in the U.S. and Canada across five distinct areas: (a) university and unit, (b) faculty, (c) students, (d) curriculum and internship, and (e) accreditation. Data were collected via a Qualtrics online survey with 67 questions sent to 125 IEP program directors with 58 total usable responses (46% return rate).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.038
GPT teacher head0.294
Teacher spread0.257 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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