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Representações da Mata Atlântica e de sua biodiversidade por meio dos desenhos infantis

2007· article· pt· W2016132357 on OpenAlex
Maria Luiza Schwarz, Lúcia Sevegnani, Pierre André

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCiência & Educação (Bauru) · 2007
Typearticle
Languagept
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsUniversité de Montréal
FundersMinistério do Meio AmbienteCritical Ecosystem Partnership Fund
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Desenhos infantis são instrumentos úteis e significativos que podem ser empregados para avaliar conhecimentos, competências, observações e conceitos de Ciência, além de possibilitar analisar a capacidade de raciocínio. Este trabalho apresenta a análise de 395 desenhos de crianças com idade entre 6 e 14 anos, habitantes de área urbana de Joinville, SC, Brasil, com o objetivo de verificar quais são os conhecimentos desse grupo social sobre a Mata Atlântica e sua biodiversidade. Foram investigados quais os ecossistemas mais representados, assim como a diversidade da flora e da fauna enfatizada. Durante a análise dos desenhos, verificamos que foram abordados quatro temas distintos: "o bom estado de conservação da Mata Atlântica", "o péssimo estado de conservação da Mata Atlântica", "comparações entre o bom e o péssimo estado de conservação da Mata Atlântica", e "recomendações para a conservação da Mata Atlântica". Os resultados mostram que 60,2% representaram "o bom estado de conservação da Mata Atlântica".

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.010

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 head0.054
GPT teacher head0.357
Teacher spread0.303 · 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