Makkan Arabic in the digital age: A sociolinguistic analysis of the representation of fricative, stop, and sibilant variation in WhatsApp text messages
Bibliographic record
Abstract
This study examines Makkan Arabic speakers’ orthographic representation of standard and colloquial variants in their WhatsApp text messages. In particular, we examine the role that speaker gender, speaker age, gender composition of conversations, and topic of discussions play in Hadari Makkans’ representation of standard and colloquial variants of the variables (th), (dh), and (Dh). Statistical analyses reveal that women favor colloquial variant stops [t] and [d], while men exhibit a preference for standard variants [θ] and [ð], particularly when conversing with other men. For (Dh), however, both women and men favor the standard variant [ðˤ]. Age also plays a role in the distribution of variants, with speakers favoring standard variants as they age. The use of fricatives [θ] and [ð] also increases when participants discuss formal topics, which suggests an implicit association between standard language and formality, despite the inherent informality of WhatsApp interactions. This study provides insights into how phonological variation is orthographically represented within a written genre designed to mimic spontaneous conversation and enriches the broader discourse on Arabic language variation and digital communication.
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How this classification was reachedexpand
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".