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Record W4206476397 · doi:10.1163/9789004459748_009

Sensorium, Sensescapes, Synaesthesia, Multisensoriality: A New Way of Approaching Religious Experience in Antiquity?

2021· book-chapter· en· W4206476397 on OpenAlexaff
Adeline Grand‐Clément

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicHistorical, Religious, and Philosophical Studies
Canadian institutionsCanadian Heritage
FundersAgence Nationale de la Recherche
KeywordsTerminologyFeelingAffect (linguistics)AestheticsField (mathematics)EpistemologySociologyHistoryPsychologyArtPhilosophyLinguisticsCommunication

Abstract

fetched live from OpenAlex

This paper aims to show that, despite the significant differences between the research approaches available to classicists and anthropologists, some notions, methods, and case studies from the field of anthropology may well prove useful and inspiring for classicists interested in the relationship between sensoria and religious experiences. These tools have the potential to help historians of ancient religions to clarify their own terminology and methodology, and to shed new light upon the documentary sources on which they rely. The first part of this chapter thus considers one particular notion that arises frequently in sensory studies: “synaesthesia”, the interplay of the senses. To what extent might this concept be relevant to the study of the religious experiences of ancient societies? And which kinds of evidence can we use to reflect upon it? The second part of the chapter will consider two (Greek) case studies in which the creation of a specific sensescape might affect the body and feelings of the worshippers. Hopefully, they will be worth reflecting on for the study of Roman religion.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.254
Teacher spread0.177 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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