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TORNAR-SE UM BUDA: ANÁLISE SEMIÓTICA DE VISUALIZAÇÕES NO BUDISMO TIBETANO

2019· article· pt· W2995702710 on OpenAlexaff
Louis Hébert, M. de F. Batista

Bibliographic record

VenueActa Semiótica et Lingvistica · 2019
Typearticle
Languagept
FieldSocial Sciences
TopicUrban and sociocultural dynamics
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Este trabalho analisa alguns aspectos do budismo Vajrayāna sob a perspectiva teórica das zonas antrópicas de François Rastier, para quem, o nível semiótico da prática social pode ser articulado em três zonas antrópicas: a identitária, a proximal e a distal. A primeira corresponde, em particular, ao indivíduo, a segunda aos congêneres e a terceira é preenchida com objetos ausentes, imaginários ou desconhecidos. Sem nuances pejorativas, o autor chama fetiches aos objetos da primeira fronteira e ídolos aos da segunda. O corpus analisado consiste, principalmente, em textos do sādhana , onde o praticante é convidado, através de visualizações complexas, a ser transformado, progressivamente, durante a sessão, em um ser iluminado, um Buda, passando, assim, em pensamento, da zona antrópica de identidade para a zona distal, através da mediação de uma divindade budista que tem o status de ídolo

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.008
Scholarly communication0.0060.002
Open science0.0000.002
Research integrity0.0000.001
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 head0.026
GPT teacher head0.332
Teacher spread0.306 · 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
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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