SOCIAL ATTITUDES AND SPEECH RATINGS
Bibliographic record
Abstract
Abstract This study examined whether social bias manipulation can influence how naïve multiage listeners evaluate second language (L2) speech. Sixty native English-speaking listeners (Montreal residents) rated audio recordings of 40 Quebec French speakers of L2 English for five dimensions of oral performance (accentedness, comprehensibility, segmental accuracy, intonation, flow) using 1,000-point continuous scales. Immediately before rating, 20 listeners heard critical comments about Quebec French speakers’ English language skills, while 20 heard positive comments. Twenty listeners (baseline group) received no manipulation. Compared to baseline listeners, positively oriented listeners (younger and older) rated four of five dimensions more favorably. However, listeners’ behavior diverged under negative bias. Compared to age-matched baseline listeners, younger listeners upgraded speakers while older listeners downgraded speakers for all targeted measures. Findings cast doubt on the relative stability of L2 speech ratings and point to the importance of social context and generational differences in untrained rater assessments of L2 speaking 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 | 0.002 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".