Morphological Integration of Urdu Loan Words in Pakistani English
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Bibliographic record
Abstract
Pakistani English is a variety of English language concerning Sentence structure, Morphology, Phonology, Spelling, and Vocabulary. The one semantic element, which makes the investigation of Pakistani English additionally fascinating is the Vocabulary. Pakistani English uses many loan words from Urdu language and other local dialects, which have become an integral part of Pakistani English, and the speakers don't feel odd while using these words. Numerous studies are conducted on Pakistani English Vocabulary, yet a couple manage to deal with morphology. Therefore, the purpose of this study is to explore the morphological integration of Urdu loan words in Pakistani English. Another purpose of the study is to investigate the main reasons of this morphological integration process. The Qualitative research method is used in this study. Researcher prepares a sample list of 50 loan words for the analysis. These words are randomly chosen from the newspaper “The Dawn” since it is the most dispersed English language newspaper in Pakistan. Some words are selected from the Books and Novellas of Pakistani English fiction authors, and concise Oxford English Dictionary, 11th edition. The results show that, when the Urdu language loan words are morphologically integrated in Pakistan English, they do not change their grammatical category. Moreover, four distinguished morphological process are identified in integration of these loan words. The results also reveal that deficit hypothesis is the main reason of this lexical borrowin.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it