Interface Between National Ideologies and the Constitution of Pakistan
Bibliographic record
Abstract
Language of State Constitutions has mainly been studied from generic, linguistic, stylistic, and discursive perspectives, however, analyzing the same from ideological view point hasn’t caught the eye or preference of most studies in general and in Pakistan in particular. The paper, with democratic concerns, concentrates on analyzing the presence of ideologies in the Constitution of Pakistan. It is exploratory in nature and analyzes genre of the Constitution of Pakistan (1973) to find out to what extent the constitution is loaded with ideological concepts and that what are the foci of such ideologies. It also delves into how ideologies are clothed in linguistic manifestation to form national views towards religion, politics, gender, power, education, rights, obligations, defense and various other “fields” and thus bring about socio-political effects. Genre analytical studies have taken a complete new turn after the introduction of elements of criticality and ideology, as in this paper. Precisely, the paper focuses on presence of ideologies in the text of the current Constitution of Pakistan and groups them under “fields of ideologies” which characterizes the constitutional genre under study. The study concludes by drawing attention to strong links between education and constitution which may be utilized to bring positive change in the society. The findings may potentially encourage similar CGA studies on constitutional genres and ideologies, around the globe.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".