<b>Kinship, Factions and Survival in Pakistani Politics</b>
Bibliographic record
Abstract
Abstract Pakistan’s political volatility is well known and oft cited as a cause for concern both regionally and internationally. The state is accused of adopting duplicitous tactics and fostering violent paramilitary organizations in its efforts to undermine Indian hegemony and internal opposition. From the outside, the persistent functioning of the state can sometimes appear to be a mystery. Managing chronic conflicting adversarial relations over a sustained period of time demands particular social and political tools that must be resilient while ensuring robust reproduction of particular types of shared interests. Such social and political tools are diverse and operate to generate both stability and instability in state political institutions. The political networks of individuals and groups that actively seek to control and manipulate state institutions are formed through different types of relationship, but one of the most publicly visible is marriage. Marriage networks offer opportunities for indirect alliances through children, siblings and other kin members in ways that need not threaten ideologically rooted affiliations, such as those created through shared political party membership. In this working paper, we focus on the communicative potential of such marriage networks through comparing village networks of landowners and the families who engage actively in electoral politics in Punjab, Pakistan. Although these findings are based on more than two decades of research carried out in rural and urban Pakistan, they remain partial, because Pakistani politics is anything but tidy or simply. Nevertheless, any attempt to analyze Pakistani politics that neglects the impact of the complex personal relationship networks is unlikely to satisfactorily explain or even describe the current political situation of the country.
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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 | 0.002 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".