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Record W4309440993 · doi:10.1111/modl.12809

Comprehensible to Whom? Examining Rater, Speaker, and Interlocutor Perspectives on Comprehensibility in an Interactive Context

2022· article· en· W4309440993 on OpenAlex
Charlie Nagle, Pavel Trofimovich, Mary Grantham O’Brien, Sara Kennedy

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

VenueModern Language Journal · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of CalgaryConcordia University
Fundersnot available
KeywordsPsychologyContext (archaeology)Cognitive psychologyContext effectLinguistics

Abstract

fetched live from OpenAlex

Abstract Comprehensibility has emerged as a useful and intuitive means of globally evaluating second language (L2) speakers in many research and instructional contexts. In most cases, L2 speakers’ comprehensibility is assessed by external listeners who do not engage in extensive communication with the speakers, even though the degree to which a speaker is comprehensible is presumably of greatest concern to their interlocutor. If comprehensibility is defined as the ease with which speakers come to understand one another, then interaction‐based assessments, which would include self and peer ratings, might provide different insight into interactive comprehensibility compared to assessments by external listeners. To examine this issue, in this study, 20 pairs of L2 English interactants rated themselves and their partner on 7 occasions distributed throughout a 17‐minute interaction encompassing 3 communicative tasks, and recordings of the interaction were subsequently presented to external raters for evaluation. Mixed‐effects models were used to compare the shape of the comprehensibility curves over time and the self, partner, and rater scores at each rating episode. Results demonstrated that self and partner assessments were always aligned, but raters consistently assigned significantly lower comprehensibility scores to the interactants. These findings have implications for how comprehensibility, and indeed other listener‐based constructs, are assessed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.294
Teacher spread0.246 · 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