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Record W4313326064 · doi:10.5430/wjel.v12n7p346

Narrative Ideology and Repercussions: Representation of the Kashmir Conflict in Modern Literature

2022· article· en· W4313326064 on OpenAlexvenueno aff
Shouket Ahmad Tilwani

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsKashmiriEmancipationChinaImpunityPoliticsIdeologyContext (archaeology)NarrativeLawGeopoliticsResistance (ecology)Armed conflictPolitical scienceHistorySociologyCriminologyLiteratureArt

Abstract

fetched live from OpenAlex

The research aims to explore the Kashmir conflict that has fractured the lives of the Kashmiri people. In the current times, the Kashmir conflict has been remarkably engaging literate circles all over the world. The conflict has been in the news worldwide for the last three decades because it may cause modern-day warfare betweenIndia, Pakistan, and China. Hence, people all over the world want to know about the situation in the region. The historical, sociological, and moral approaches by Wilbur Stewart Scott are used to grasp the context of the selected novelsThe Collaborator (2012) and Book of Gold Leaves (2015). Mirza Waheed, as an eyewitness, sketched the novels on the sufferings of Kashmiris, engaging daily with a god of death because of the conflictual situation. This situation has been routined since the invasion and occupation of the land by the three nuclear armament-holding neighbors, India, Pakistan, and China, immediately after the emancipation of the first two from their British colonial masters in 1947. The political scenario of Jammu and Kashmir became murkier in 1988 and onwards when India intensified its military operations to quell the armed resistance movement for “Azadi” (freedom) of land. The modern Kashmiri literature roots out the sentiment of freedom; India gave impunity to any draconian tactics in the name of rules that justified any inhuman treatment of custodial killing, torture, rape, etc. As a result, more than three lac women are dead, approximately 10000 are missing, and thousands are languishing in jails.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0210.034
Scholarly communication0.0120.010
Open science0.0020.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.302
Teacher spread0.288 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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