A Multidimensional Analysis of Pakistani Legal English
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
The present study aims to investigate linguistic variation among genres of Pakistani Legal English by applying multidimensional analysis. In a legal context, language performs different functions. This results in a variety of textual categories on the basis of purpose of communication and linguistic properties. In order to recognize the linguistic properties of any individual genre, a comparative study of genre categories is essential. The study has been conducted on the sample of eight Pakistani Legal genres based on around two million words. Data have been analyzed by applying Biber’s (1988) model of Multidimensional analysis. Findings reveal variation in linguistic patterns. All categories have been found significantly different along each dimension. It indicates that legal language is not a homogeneous phenomenon. It has a variety of linguistic features associated with different legal genres, so it must be viewed in terms of goal, purpose, audience and context (variable which affect the language choice).
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 | 0.002 | 0.226 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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