Linguistic Convergence and Divergence in the Use of the Third Person Singular Feminine Suffix among the Qassimi Speech Community in Riyadh
Bibliographic record
Abstract
This study examines the linguistic impact of dialect contact on Qassimi Arabic (QA) speakers residing in Riyadh. Focusing on the morphophonemic feature of the third-person singular feminine suffix (-ah/-ha), the research investigates patterns of convergence and divergence through a variationist sociolinguistic lens. Data from sociolinguistic interviews with 32 QA speakers in Riyadh were analyzed using SPSS. Findings indicate a prevalent use of the non-standard variant [-ah], suggesting a strong preservation of traditional linguistic features among QA speakers despite exposure to other Saudi dialects. This was explained by the concentration of QA speakers in particular neighborhoods creating ethnic enclaves that restrict exposure to other Saudi dialects and thus preserving pre-migration speech patterns. The suffix’s morphophonemic function and lack of social or symbolic meaning also had a role in its preservation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".