How do attention-shift and foreign language anxiety interact with objective and subjective measures of fluency?
Why this work is in the frame
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Bibliographic record
Abstract
The present study investigated whether a distinct link exists between attention-shift, foreign language anxiety (FLA) and both a subjective and an objective measure of oral fluency. Participants were 34 French first language (L1) English second language (L2) speakers. Oral production data were collected through a picture-cued narration task and analysed using both oral fluency measures. We used a measure of attention-shift capacity and a measure of FLA. Results first show strong correlations between both fluency measures. Additionally, both measures of fluency were negatively correlated with FLA and attention-shift. However, multiple regression analyses indicated that only the subjective measure was explained by both attention-shift capacity and FLA, the objective one only being explained by FLA. The results suggest that subjective measures, while highly correlated with objective ones, may detect qualities of oral fluency not detected by objective measures.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it