Semantic Change in Urdu: A Case Study of “Mashkoor”
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
Languages are dynamic in nature and Urdu language is no exception. This study aims to probe semantic change in Urdu lexis and focuses on the meaning of the word “mashkoor” (thanked). For this study, Urdu dictionaries, a corpus of 25 million Urdu words and a questionnaire have been used. Our analysis determines that “mashkoor” has shifted meanings from being “thanked” to “thankful”. The results depict that the grammarians, lexicographers or the teachers are not the authority to decide correct usage in a language but it is the prerogative of users as well. The present study strengthens the idea that Urdu language has changed with the passage of time. It also proposes that Urdu dictionaries should be corpus based and include the current usage by the masses to incorporate the latest changes. This study will serve for other researchers as a springboard to further explore the other aspects of Urdu language.
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 | 0.001 | 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) | 0.000 | 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 it