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A CONTRIBUIÇÃO DOS CONTOS DE FADAS NO PROCESSO DE ENSINO EAPRENDIZAGEM DAS CRIANÇAS

2018· article· en· W2922171559 on OpenAlex

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

VenueColloquium humanarum · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicScience and Education Research
Canadian institutionsBibliographical Society of Canada
Fundersnot available
KeywordsTheme (computing)StorytellingElaborationPsychologyValue (mathematics)Dimension (graph theory)Process (computing)Reflection (computer programming)EpistemologySociologyPedagogyHumanitiesPhilosophyComputer scienceLinguisticsNarrative

Abstract

fetched live from OpenAlex

This work has as its theme the contribution of fairy tales in the process of learning of children, addressing in a significant way the importance that the fairy tales exert in the pedagogical dimension and in what aspects can favor the development of the child. It presents a qualitative approach that favors reflection, analysis and interaction about the theories and hypotheses raised.The question that motivated the choice of this theme was: How fairy tales can contribute to the development of the child. The bibliographical research was the one that supported the whole elaboration of this work, in which were used conceptions of important authors of children's literature. From the literary review, it was possible to perceive that, although storytelling presents itself as a rich medium for the development of children's abilities, teachers are generally unaware of their value as a support in the teaching-learning process.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.044
GPT teacher head0.452
Teacher spread0.409 · 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