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Record W2123754104 · doi:10.1017/s1366728914000832

Flawed self-assessment: Investigating self- and other-perception of second language speech

2014· article· en· W2123754104 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

VenueBilingualism Language and Cognition · 2014
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsFluencyPsychologySelf-assessmentPerceptionStress (linguistics)CognitionCognitive psychologyLinguisticsComputer scienceSocial psychologySpeech recognition

Abstract

fetched live from OpenAlex

This study targeted the relationship between self- and other-assessment of accentedness and comprehensibility in second language (L2) speech, extending prior social and cognitive research documenting weak or non-existing links between people's self-assessment and objective measures of performance. Results of two experiments (N = 134) revealed mostly inaccurate self-assessment: speakers at the low end of the accentedness and comprehensibility scales overestimated their performance; speakers at the high end of each scale underestimated it. For both accent and comprehensibility, discrepancies in self- versus other-assessment were associated with listener-rated measures of phonological accuracy and temporal fluency but not with listener-rated measures of lexical appropriateness and richness, grammatical accuracy and complexity, or discourse structure. Findings suggest that inaccurate self-assessment is linked to the inherent complexity of L2 perception and production as cognitive skills and point to several ways of helping L2 speakers align or calibrate their self-assessment with their actual performance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.773

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.341
Teacher spread0.322 · 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