Transforming a praetorian polity: the political economy of democratization in Pakistan
Bibliographic record
Abstract
This paper analyzes the hegemonic role of the military vis-à-vis elected civilian governments in Pakistan from the vantage point of institutional political economy. Absence of “good governance” on the part of elected civilian governments is often depicted as the key underlying factor that allows the military to maintain its dominance over state and society. In sharp contrast, we argue that the emphasis on “good” governance as a pathway to democratic consolidation ignores socio-economic and institutional factors which facilitate the successful reproduction of Pakistan’s militarized hegemonic order. The paper argues that the military hegemony is rooted in the prevailing political economic structure mediated by forces of imperialism. By drawing from Erik Olin Wright’s (2010. Envisioning Real Utopias) tripartite conceptual scheme of “symbiotic,” “interstitial,” and “ruptural” transformation strategies, we offer a new framework to analyze processes of democratic transformation in Pakistan. We contend that the consolidation of democracy and civilian supremacy mandates a shift away from a narrow focus on governance to transformative politics. The latter has to be centered around an alternative hegemonic conception counterposed to the established military-centric order that would incorporate aspirations of socio-spatially and economically deprived segments from the ethnic peripheries, as well as progressive and working-class constituencies within metropolitan Pakistan.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".