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 The term “fluency” is used in two different ways in relation to second language speech. Whereas laypeople often equate fluency with proficiency in a given language, researchers define fluency as a speaker’s ease or fluidity in producing spoken language at a specific time point. This discrepancy in definitions has been problematic, especially when relying on ratings provided by naïve raters. This study seeks to determine whether “fluency” ratings differ from “fluidity” ratings assigned to 48 speech stimuli produced by native and non-native speakers of German. Samples were rated by participants from three distinct listener groups: native German listeners, second language (L2) German listeners, and non-speakers of German. On the surface, results reveal no significant differences along the two continua (“fluency” or “fluidity”). All groups rated native speakers as more fluent, and second language listeners were harshest in their ratings. Nonetheless, L2 listeners who rated speech samples along the “fluency” scale relied upon speech measures not associated with ease of speaking when compared with L2 listeners who rated the same samples for “fluidity.” Although listeners in all groups were most sensitive to speakers’ speech rate and use of filled pauses, native listeners and non-speakers relied more on temporal measures when they rated speech along the “fluidity” scale. These combined results thus indicate that “fluidity” may be the better term to use in future research relying on naïve listeners’ ratings of perceived fluency.
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it