The Identification of English Consonants by Native Speakers of Italian
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
This study examined the identification of English consonants in noise by native speakers of Italian. The effect of age of first exposure to English was evaluated by comparing three groups of subjects who continued to use Italian relatively often but differed according to their age of arrival (AOA) in Canada from Italy (early: 7, mid: 14, late: 19 years). The subjects in the late group made more errors identifying word-initial consonants than subjects in the early group did; however, the effect of AOA was nonsignificant for word-final stops. The effect of amount of native language (L1) use was evaluated by comparing two groups of early bilinguals who were matched for AOA (mean = 7 years) but differed according to self-reported percentage use of Italian (early: 32%, early-low: 8%). The early bilinguals who used Italian often (early) made significantly more errors identifying word-initial and word-final consonants than native English (NE) subjects did, whereas the early bilinguals who used Italian seldom (early-low) did not differ from the NE subjects. The subjects' phonological short-term memory was estimated by having them repeat Italian non-words. This was done in an attempt to identify the source of individual differences. The nonword repetition scores were in fact found to independently account for 15% of the variance in subjects' errors identifying word-final English consonants and 8% of the variance for word-initial consonants.
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 | 0.000 | 0.000 |
| 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) | 0.003 | 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