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Record W3169182844 · doi:10.18357/bigr22202120196

Borders, Citizenship, and the Local: Everyday Life in Three Districts of West Bengal

2021· article· en· W3169182844 on OpenAlexvenueno aff
Shibashis Chatterjee, Surya Sankar Sen, Mayuri Banerjee

Bibliographic record

VenueBorders in Globalization Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsTerritorialityConceptualizationSociologyCitizenshipSovereigntyIdentity (music)State (computer science)Gender studiesGeographyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Borders have been considered essential to understanding the self and the other, with identities on either side established through functions of exclusion and inclusion. These processes, initially considered to be the preserve of the state as exercised through its policies of border management, also exist in tandem or in an asynchronous manner at the local level. Constituted of processes of identification and networks of interdependences, localized construals of the borderland and subsequently positioned engagements, comes to shape notions of accessibility and restriction as well as perceptions of the “other”. These engagements are not always reflective of statist positions on the border which are often uniform in the conceptualization of its capacity to contain. They subsequently come to reflect the variations of divergent historical and locational realities. There is a need to further extend the analysis of borderlands beyond statist framings as passive recipients of policy as well as recognize the critical positioning of local adaptive processes as antithetical to state demarcations of territoriality and sovereign authority. Based on a survey of three districts in the state of West Bengal, India, this study posits an analysis of the multiple perceptions both within and outside of statist framings of borderland identity and territoriality, which color its inhabitants’ understanding of the border and perceptions surrounding and interactions with the communities that lie beyond it.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0070.005
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.317
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBorders in Globalization ReviewSame topicSouth Asian Studies and ConflictsFrench-language works237,207