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Record W2113825009 · doi:10.7202/1007166ar

Neurosémiotique et bouddhisme

2011· article· fr· W2113825009 on OpenAlexvenueno aff
Daniel S. Larangé

Bibliographic record

VenueProtée · 2011
Typearticle
Languagefr
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyConscience

Abstract

fetched live from OpenAlex

La neurosémiotique s’intéresse au(x) bouddhisme(s) dans le cadre d’un dialogue entre la science et la conscience. La neurosémiotique envisage un rapport fonctionnel entre la représentation qui découle du rapprochement Sa/Sé et l’émergence d’un état de conscience, de sorte que la manière de penser le réel détermine la façon de le vivre. Il en découle un paradoxe qui consiste à envisager la fiction comme précédant la réalité. Dès lors, la neurosémiotique propose d’expliquer l’émergence du sens à partir de l’élaboration de champs énergétiques formant une structure tensive articulant la mimesis à la semiosis à travers la diegesis. Le questionnement du rapport du sujet observant à l’objet observé intègre les données de la physique quantique afin d’expliciter le phénomène de participation au réel avec lequel le cerveau entre en connexion dans sa quête de compréhension. Cela conduit donc à s’interroger sur la nature même de la conscience qui s’auto-organise dans une coproduction conditionnée. Le dialogue interculturel qui s’établit à partir de résonances entre les investigations de la science et les pratiques du bouddhisme finit par devenir transculturel dans la mesure où la conscience de la science a son origine dans l’absence de ses assises, car l’univers évacue peu à peu le sujet et l’objet qui le forment dans le je(u) complexe des représentations en régime sémiotique.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.027
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.178
GPT teacher head0.374
Teacher spread0.196 · 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 designTheoretical or conceptual
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
Published2011
Admission routes1
Has abstractyes

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