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Record W2322386395 · doi:10.1558/rsth.v33i1.65

What The Sister Knew

2014· article· en· W2322386395 on OpenAlexaff
Brenda E. F. Beck

Bibliographic record

VenueReligious Studies and Theology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSisterBrotherLegendAdventureReciprocity (cultural anthropology)GenealogyGirlSiblingHistoryArtSociologyLawArt historyPsychologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

This essay looks beneath the surface of the “Annanmar Katai,” a major folk epic from Tamilnadu, to discover how the lone female in a set of three siblings leads a life very different from that of her two elder brothers. In the absence of their parents, these men enjoy their life as twin rulers of a small kingdom. Meanwhile their sister sits alone on her swing inside the family palace. Her brothers undertake many wondrous adventures while she slowly develops her own ability to see into the future through dreams. Gradually, however, this unmarried girl discovers that her brothers are not keeping their side of the traditional sibling contract. Brothers should listen to and protect their female siblings. Their sisters (especially virgin ones) will then reciprocate by magically transferring their stored-up powers to their brothers’ swords. When, in this folk legend, two powerful brothers withhold information, their sister starts to keep her insights secret too. The family kingdom now starts to fall apart as this key understanding between a sister and her brothers grows frayed. In sum, the essay reveals the major importance given to the maintenance of a positive, life-long brother-sister bond of reciprocity in traditional Tamil culture.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.003
Scholarly communication0.0050.007
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0280.009

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 head0.300
Teacher spread0.286 · 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
Published2014
Admission routes1
Has abstractyes

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