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Record W4400315579 · doi:10.26512/rbla.v16i1.51931

construção social de tempo baseado em eventos nas culturas indígenas Awetý, Kamaiurá e Huni Kuĩ

2024· article· pt· W4400315579 on OpenAlexaff
Vera da Silva Sinha, Wary Kamaiura Sabino, Joaquim Paulo de Lima Kaxinawa

Bibliographic record

VenueRevista Brasileira de Linguística Antropológica · 2024
Typearticle
Languagept
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Nas culturas Huni Kuĩ, Awetý, Kamaiurá, o tempo é concebido em termos de eventos sociais e ambientais; linguisticamente, tal concepção se materializa em palavras e expressões usadas no cotidiano, em atividades e práticas culturais, quando os falantes se referem a fatos que necessitam de marcas temporais, como planejar festas, plantios, colheitas e até a organização de um dia típico qualquer. Nesse contexto, o presente estudo trata de como se dá a lexicalização e a indexação de intervalos de tempo nas línguas e culturas enfocadas, através de um inventário linguístico de marcas temporais relativas aos estágios da vida, divisões do dia e da noite e intervalos sazonais que norteiam a vida social. Para tanto, o texto discorre sobre como o sol, a lua e as estrelas estão inseridos no processo de indexicalização de tempo baseado em eventos; como números, mãos, dedos, nós em uma corda e marcas em madeira são utilizados como indexicalizadores temporais; e como calendários híbridos e outros aspectos culturais representam intervalos de tempo baseados em eventos nessas línguas e culturas.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0030.006
Scholarly communication0.0070.006
Open science0.0010.003
Research integrity0.0010.001
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 head0.035
GPT teacher head0.372
Teacher spread0.338 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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