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Record W3197254746 · doi:10.1177/24557471211021507

Land as an Intermittent Commodity: Ethnographic Insights from India’s Urban–Agrarian Frontiers

2021· article· en· W3197254746 on OpenAlexaff
Sarasij Majumder, Shubhra Gururani

Bibliographic record

VenueUrbanisation · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsYork University
Fundersnot available
KeywordsCommodificationEconomicsLand grabbingAgrarian societyExpropriationUrbanizationCasteIndustrialisationPolitical economyEconomic systemMarket economySociologyGeographyPolitical scienceEconomic growthAgricultureLaw

Abstract

fetched live from OpenAlex

Drawing on their respective ethnographies of urbanisation in Gurgaon (now known as Gurugram) and thwarted industrialisation in Singur, the authors argue that plots of land owned by smallholders are intermittent commodities. Following Igor Kopytoff’s lead, they focus on commoditisation as a process and adopt a biographical approach to consider the social life of land. The article contends that individually owned plots potentially go in and out of circulation but never get fully commodified, nor do they remain fully non-commodified. With the rising speculative value of land, neither market price nor monetary compensation fully substitutes land ownership. Hence, the landholders express regret and even resentment on having to part with their land. The ambivalence speaks, in part, to the complex attributes of land and the relations of authority, distinction and status associated with it. To maintain their caste-based status, the landowners use land as leverage. They hold on to land or demand better compensation to reiterate the land–caste–power nexus spatially.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.999

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 communication0.0000.001
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 head0.015
GPT teacher head0.252
Teacher spread0.237 · 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
Published2021
Admission routes1
Has abstractyes

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