MétaCan
Menu
Back to cohort
Record W4295706216 · doi:10.18732/hssa82

Gameplay as Foreplay at a Medieval Indian Court

2022· article· en· W4295706216 on OpenAlexvenueno aff
Jacob Schmidt-Madsen

Bibliographic record

VenueHistory of Science in South Asia · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArtPolitical science

Abstract

fetched live from OpenAlex

This study focuses on the singular courtly game of phañjikā described in the 12th-century Mānasollāsa attributed to King Someśvara III of the Western Cālukya Empire. It shows that phañjikā belongs to the family of cruciform race games, which also counts the famous games of caupaṛ and paccīsī among its members. Phañjikā, however, predates the earliest evidence for both of those games by several centuries, and should therefore be considered an early indication of the popularity that cruciform race games would come to enjoy in elite and royal households from at least the 15th century onward. The study also shows that phañjikā did not enjoy the same status at court as other board games, such as chess and backgammon, also described in the Mānasollāsa. It was primarily associated with the women at court, and only engaged in by the king for the pleasure of witnessing the passionate emotion that it stirred in them. Based on the low status of the game, and the prevalence of race games in all levels of society, the study argues that phañjikā was likely an elaborate courtly adaptation of a simpler folk game. This would explain its absence from the literature outside the Mānasollāsa, as well as its many correspondences with a wide range of cruciform, square, and single-track race games only documented in more recent sources. The study suggests that more scholarly attention should be paid to the regional literatures of India, as they developed in the first half of the 2nd millennium CE, for a more detailed understanding of the early history of medieval Indian race games to be arrived at.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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 score0.863
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.236
Teacher spread0.212 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueHistory of Science in South AsiaSame topicFolklore, Mythology, and Literature StudiesFrench-language works237,207