Geminate attrition in the speech of Arabic–English bilinguals living in the United States
Bibliographic record
Abstract
This study explores the phenomenon of language attrition. Specifically, we investigate the phonetic properties of consonant gemination across three groups of speakers of Palestinian Arabic: monolinguals (i.e., native speakers born in Palestine who have lived there their entire life, n = 5), late bilinguals (i.e., speakers born in Palestine who emigrated to the US during their teens, n = 6), and heritage speakers (i.e., speakers of Palestinian descent, born in the US and who speak both English and Arabic in their daily lives, n = 7). All speakers were in their mid-1920s. The participants were tested using a delayed word repetition task. The stimuli comprised 158 bi-syllabic Arabic minimal and near-minimal pairs (e.g., /ħam:aːm/ “bathroom” versus /ħama:m/ “pigeon”) including long and short stops, fricatives, and sonorants. We controlled for stress and syllabic position. Distractors were also included. The acoustic analysis is underway, and consists of manually aligning the target consonants, extracting the mean consonant duration and comparing it across groups. Additional measures include voicing, aspiration, and formant transitions. The findings will enable us to address the question whether universal phonetic factors (from the perspective of Markedness Theory) have an effect on degree of attrition by specifically comparing consonants from different voicing categories and manners of articulation.
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.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".