Testing the malleability of teachers’ judgments of second language speech
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.
Bibliographic record
Abstract
Abstract This study examined whether a negative social bias can influence how teachers evaluate second language (L2) speech. Twenty-eight teachers of L2 German from Western Canada – 14 native speakers (NSs) and 14 proficient non-native speakers (NNSs) – rated recordings of 24 adult L2 learners of German across five speech dimensions (accentedness, comprehensibility, vowel/consonant accuracy, intonation, flow) using 1,000-point scales. Immediately before rating, half of NS and NNS teachers heard critical comments about undergraduate German students’ language skills, while the other half heard no biasing comments. Under negative bias, while the NNS teachers provided favorable evaluations across all five measures, NS teachers followed suit for only intonation and flow, downgrading L2 speakers’ accentedness, comprehensibility, and vowel/consonant accuracy. Findings call into question the relative stability of L2 speech ratings and highlight the importance of social context and teacher status as native versus non-native speakers of the target language in assessments of L2 speaking 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 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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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