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Record W4285731491 · doi:10.1111/joac.12503

(Landlord) Theory from the South: Empire and estates on a Punjabi Frontier

2022· article· en· W4285731491 on OpenAlexafffund
Shozab Raza

Bibliographic record

VenueJournal of Agrarian Change · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Toronto
FundersJackman Humanities Institute, University of TorontoInternational Development Research CentreWenner-Gren Foundation
KeywordsColonialismAgrarian societyFrontierScholarshipEmpireSociologyModernization theoryHegemonyLandlordPolitical economyLawPolitical scienceAgriculturePoliticsHistory

Abstract

fetched live from OpenAlex

Abstract Theory has occasionally shaped agrarian transformations. Utilitarian theory, for instance, influenced British colonial land revenue policies, while modernization theory spurred, via the Green Revolution, the development of capitalist farming across the global South. Yet scholarship, when it has probed the mediation of theory in agrarian change, has largely centred on the intellectual activities of Western figures. In this paper, I examine an under‐appreciated theorizing actor: landlords in the global South. I explore landlords' concept‐work in the former “Punjab Frontier,” a region where Baloch chiefs collaborated with the British Raj to acquire localized magisterial powers, a paramilitary apparatus, and immense “landed estates” ( jagirs ). To overcome various crises, certain chiefs engaged with various imperial concepts—namely, property, race, progress, contract, and freedom—and re‐arranged their estates. By showing how these elites creatively embraced these concepts to maintain a colonial‐fortified hegemony, I also challenge those who overstate the emancipatory and decolonial possibilities of theory from the South.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.198
Teacher spread0.165 · 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 designObservational
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

Citations5
Published2022
Admission routes2
Has abstractyes

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