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Record W2980901872 · doi:10.1111/joac.12338

Agrarian class struggle and state formation in post‐colonial Pakistan, 1959–1974: Contingencies of <i>Mazdoor Kisan Raj</i>

2019· article· en· W2980901872 on OpenAlexfundno aff
Noaman G. Ali

Bibliographic record

VenueJournal of Agrarian Change · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsPeasantAgrarian societyState (computer science)Leasehold estatePolitical economyColonialismPoliticsPower (physics)Class conflictRuling classPolitical scienceIntervention (counseling)Land tenureDevelopment economicsAgrarian reformSociologyEconomicsGeographyLawAgriculture

Abstract

fetched live from OpenAlex

Abstract State formation in post‐colonial societies is often explained with reference to the roles of elites. In Pakistan, landed elites continue to dominate the rural political economy through informal and formal institutions, but the history of its largest peasant movement shows how agrarian class struggle can change the institutional forms and functions of power. The Hashtnagar peasant movement achieved lasting de facto land and tenancy reforms in north‐western Pakistan in the 1970s through forcible land occupations that were regularized by state intervention. I argue that although divisions among elites were important, the state intervened in favour of peasants due to the rising organizational power of tenants and landless labourers under the centralized leadership of the radical Mazdoor Kisan Party. Agrarian class struggle weakened the informal power of landed elites and gave rise to institutions of peasant power. However, other fractions of the ruling class sought to undermine their landed opponents while co‐opting the militancy of the peasant movement by strengthening state institutions to intervene in favour of upwardly mobile tenants. The latter were separated from poorer peasants and the landless, thus demobilizing the movement.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.936

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.028
GPT teacher head0.292
Teacher spread0.264 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations18
Published2019
Admission routes1
Has abstractyes

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