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
Socio-indexical cues and paralinguistic information are often beneficial to speech processing as this information assists listeners in parsing the speech stream. Associations that particular populations speak in a certain speech style can, however, make it such that socio-indexical cues have a cost. In this study, native speakers of Canadian English who identify as Chinese Canadian and White Canadian read sentences that were presented to listeners in noise. Half of the sentences were presented with a visual-prime in the form of a photo of the speaker and half were presented in control trials with fixation crosses. Sentences produced by Chinese Canadians showed an intelligibility cost in the face-prime condition, whereas sentences produced by White Canadians did not. In an accentedness rating task, listeners rated White Canadians as less accented in the face-prime trials, but Chinese Canadians showed no such change in perceived accentedness. These results suggest a misalignment between an expected and an observed speech signal for the face-prime trials, which indicates that social information about a speaker can trigger linguistic associations that come with processing benefits and costs.
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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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