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Record W2965104151 · doi:10.1075/ijcl.17088.pic

An introduction to the ANAWC

2019· article· en· W2965104151 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Corpus Linguistics · 2019
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsComputer scienceResource (disambiguation)Augmentative and alternative communicationTranscription (linguistics)Natural language processingLinguisticsHuman–computer interaction

Abstract

fetched live from OpenAlex

Abstract This paper presents an overview of the Augmentative and Alternative Communication (AAC) and Non-AAC Workplace Corpus (ANAWC) ( Pickering & Bruce, 2009 ). The corpus is the first resource of its kind that makes it possible to systematically study the typical language patterns of both AAC users and comparable non-AAC users in the workplace. We discuss the origin of the corpus and give an account of the methodology used for its collection and transcription. We also introduce several publications that demonstrate the novel qualitative and quantitative findings that can be generated on the basis of the corpora. This kind of research will be crucial to guide future developments in AAC development for workplace applications.

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.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.040
GPT teacher head0.447
Teacher spread0.407 · 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