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Record W2921536862 · doi:10.1080/14746689.2019.1565323

Memories of violence: Of emotional geographies and planning in post-Partition Delhi, 1948–62

2018· article· en· W2921536862 on OpenAlexaff
Aprajita Sarcar

Bibliographic record

VenueSouth Asian Popular Culture · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Studies and Diaspora
Canadian institutionsQueen's University
Fundersnot available
KeywordsRefugeeConversationPartition (number theory)SociologyEveryday lifeContext (archaeology)Media studiesGender studiesHistoryPolitical scienceLawCommunicationArchaeology

Abstract

fetched live from OpenAlex

This article engages with the messy streets of post-Partition Delhi. The author engages with a relatively understudied facet of the Partition: its impact on the everyday life of a city. Through physical sites which carried imprints of former inhabitants, to letters that refugees wrote to express their anxieties, the article constructs identities that were forged in the everyday life of Delhi. Questions of ownership, self-making, and governance help answer how the trauma of riots was negotiated in mundane paper trails. The essay is divided into two parts. The first half describes the emotional topography of the city, with an eye on the aspirations of the refugee. It describes the emotional city the refugee encountered. The second half addresses the way the refugee talks back and creates her own emotional landscape. The first master plan of the city enacted in 1962 provides the context for this conversation.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.504

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.233
Teacher spread0.216 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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