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Record W2010398948 · doi:10.7202/015310ar

Rêves et visions chez les Amérindiens : " produire un ours "

2003· article· fr· W2010398948 on OpenAlexvenueno aff
Barbara Tedlock

Bibliographic record

VenueAnthropologie et Sociétés · 2003
Typearticle
Languagefr
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

Rêves et visions chez les Amérindiens : "produire un ours " De nombreuses sociétés amérindiennes font des distinctions entre de multiples types de rêves, en particulier le rêve " lucide " dans lequel les personnes endormies prennent conscience qu'elles sont en train de rêver mais demeurent en état de rêve et dirigent les actions de leurs âmes, de leurs ombres, de leurs sois ou de leurs doubles. Les peuples autochtones ont également développé des traditions narratives et des prestations musicales complexes, ainsi que des méta-commentaires sophistiqués, à propos des processus et des produits du rêve. Leurs systèmes classificatoires et leurs theories du rêve sont étroitement liés à des conceptions de la personne et à des codes linguistiques spécifiquement locaux. Le récit de rêve, de vision ou de mythe s'accompagne de l'usage marqué de certaines particules linguistiques, qui exigent du narrateur qu'il adopte une attitude particulière envers la valeur de vérité d'une affirmation. Le statut épistémologique du rêve dépend de ces particules, appelées " indicateurs " (evidentials).

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.007
Scholarly communication0.0020.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.171
GPT teacher head0.572
Teacher spread0.401 · 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

Citations9
Published2003
Admission routes1
Has abstractyes

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