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Record W2462634390 · doi:10.1080/02666030.2016.1182326

From Fear to Hostility: Responses to the Conquests of Madurai

2016· article· en· W2462634390 on OpenAlexaff
Ajay K. Rao

Bibliographic record

VenueSouth Asian Studies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicIndian and Buddhist Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsThroneAncient historySanskritHinduismCONQUESTHistorySouth asiaRupeePower (physics)DramaLiteratureArtReligious studiesLawPoliticsPhilosophyPolitical science

Abstract

fetched live from OpenAlex

<p>In the second decade of the fourteenth century, twenty years after ascending the throne in Delhi, Sultan ʿAlāʾ al-Dīn Khaljī sent the former slave Malik Kāfūr on a series of southern campaigns, resulting in attacks on Warangal, Dvarasamudra, and Madurai. Even though the ostensible purpose was plunder, and Malik Kāfūr’s forces reinstated the defeated local kings while extracting tribute, these southern expeditions represent a dramatic expansion of Indo-Islamic power into the Deccan. Madurai, further south and controlled by the Pandyas, proved to be more recalcitrant than the other sites. Malik Kāfūr attacked Madurai in 1311 and sacked the nearby Srirangam temple, but it was not Malik Kāfūr but Ulugh Khān in 1323 who finally brought Madurai under Sultanate control. Madurai became independent between 1333 and 1334 and was ultimately conquered again by Vijayanagara forces in 1371. In this paper, I explore two Sanskrit literary responses to the conquests of Madurai that differ remarkably in genre and mood. A careful juxtaposition and analysis of the two poems presents a challenge to the dominant scholarly approach to such narratives as ‘epics of resistance’ and the concomitant assumption that representation of conflict reveals the existence of mutually exclusive and hostile ‘Hindu’ and ‘Muslim’ cultures.</p>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.001

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 head0.060
GPT teacher head0.286
Teacher spread0.226 · 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.

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

Citations1
Published2016
Admission routes1
Has abstractyes

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