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Record W2921891621 · doi:10.18542/nra.v4i1.6423

Narrativas contadas na Ilha de Cotijuba (PA): as poéticas do imaginário entre as memórias e as paisagens insulares

2016· article· pt· W2921891621 on OpenAlexaff
Carla Melo De Vasconcelos, Renilda do Rosário Moreira Rodrigues Bastos

Bibliographic record

VenueNova Revista Amazônica · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicUrban and sociocultural dynamics
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Neste artigo procuramos tecer um diálogo entre as Narrativas Orais contadas sobre a ilha de Cotijuba e as imagens que delas suscitam. As narrativas orais, enquanto acontecimentos e materialidade são tecidos no cotidiano local das paisagens insulares do estado do Pará. Seus desdobramentos em memórias e imaginários envolvem a comunidade de narradores e ouvintes de Cotijuba. Assim, busca-se traçar uma atitude mais reflexiva dos encontros entre o imaginário poético, que as narrativas evocam, e as memórias dos narradores da ilha de Cotijuba, por meio das representações produzidas durante o trabalho de campo. Neste mergulho, buscamos utilizar perspectivas de estudos das disciplinas ministradas no Programa de Pós- Graduação em Linguagens e Saberes da Amazônia, da Universidade Federal do Pará do campus de Bragança, da linha de pesquisa Memória e Saberes Interculturais da turma de 2015- e, também, dos estudos etnográficos durante a pesquisa de campo. Partindo destes princípios esta pesquisa procura contribuir de forma científica e poética com a tessitura do ato de contar histórias, e por meio deste perceber as narrativas locais em fontes orais na construção da memória, do imaginário e da paisagem da ilha de Cotijuba.

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)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.007
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.034
GPT teacher head0.329
Teacher spread0.295 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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