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Record W4391498838 · doi:10.1002/9781119357124.ch2

“Come, and Cry, Because <i>ʿAshura</i> Is Today”

2021· other· en· W4391498838 on OpenAlexaff
Karen G. Ruffle

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicAfrican history and culture analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The short, rhyming nauhah poem is composed using accessible language and imagery, often with the goal of invoking tears and physical grief from Shi‘a through vignettes focusing on singular incidents during or in the aftermath of the battle of Karbala. This chapter takes a particular focus on the role of the feminine voice and emotions in Shi‘i devotional literature. The first nauhah incites the performance of matam , whereas the second is explicitly normative in tone, using the language of prayer to remind and explain to Shi‘a why their faith is superior. Sitting in living rooms, on the roof-top while trying to stay cool during hot summer nights, whiling away during the first days of Muharram as the anticipation builds for the intense days from 6 Muharram and after, stories about miracles performed by the Fourteen infallibles abound in South Asian Shi‘ism.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.008
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.003

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 head0.275
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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