LEXICAL PROFILES OF COMPREHENSIBLE SECOND LANGUAGE SPEECH
Bibliographic record
Abstract
This study examined contributions of lexical factors to native-speaking raters’ assessments of comprehensibility (ease of understanding) of second language (L2) speech. Extemporaneous oral narratives elicited from 40 French speakers of L2 English were transcribed and evaluated for comprehensibility by 10 raters. Subsequently, the samples were analyzed for 12 lexical variables targeting diverse domains of lexical usage (appropriateness, fluency, variation, sophistication, abstractness, and sense relations). For beginner-to-intermediate speakers, comprehensibility was related to basic uses of L2 vocabulary (fluent and accurate use of concrete words). For intermediate-to-advanced speakers, comprehensibility was linked to sophisticated uses of L2 lexis (morphologically accurate use of complex, less familiar, polysemous words). These findings, which highlight complex associations between lexical variables and L2 comprehensibility, suggest that improving comprehensibility requires attention to multiple lexical domains of L2 performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".