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Record W2789886855

Together Without Consensus: Class, Emotions and the Politics of the Rule of Law in the Lawyers’ Movement (2007-09) in Pakistan

2018· article· en· W2789886855 on OpenAlexfundno aff
Salman Hussain

Bibliographic record

VenueCUNY Academic Works (City University of New York) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
FundersMinistry of DefenseIndia Diabetes Research FoundationSocial Science Research CouncilCity University of New YorkSocial Sciences and Humanities Research Council of CanadaLahore University of Management SciencesNational Science Foundation
KeywordsPoliticsLawRule of lawClass (philosophy)Movement (music)Political scienceComputer scienceArtificial intelligencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

This dissertation is an ethnographic examination of how political emotions, historical memory and notion(s) of the rule of law are mobilized in postcolonial Pakistan. It examines how liberal legality (the rule of law, judiciary and courts) and discourses of rights have become popular hegemonic languages for mobilizing political protests and legal claims in South Asia. In particular, the dissertation studies a protest movement, the Lawyers’ Movement for the Restoration of Judiciary and Democracy (2007-09), that was led by the lawyers and their allied educated and professional middle-classes, and investigates how the lawyers successfully galvanized Pakistanis against the then prevalent military rule by formulating appeals to the rule of law and constitutionalism and led their historic bloc to restore the higher judiciary. Famously defined as the societies in which colonial law exercised only domination and never hegemony, this dissertation further examines how liberal legality and rights discourses have, in fact, become hegemonic and while managing populations and emotions, they have also enabled new sites of popular mobilization, protest and agitation in postcolonial South Asia.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.296
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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