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Afinal, o que querem os bebês?

2021· article· pt· W4392972353 on OpenAlexaff
Gabriela Guarnieri de Campos Tebet, Anete Abramowicz

Bibliographic record

VenueDebates em educação · 2021
Typearticle
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsPhilosophyEpistemologyHumanities

Abstract

fetched live from OpenAlex

Este artigo visa discutir o bebê como categoria analítica a partir de algumas ideias de Gilles Deleuze sobre a diferença. Utiliza-se o conceito de multidão retomado por Antonio Negri, Michael Hardt e Paolo Virno e as ideias de Fernand Deligny sobre o agir e querer. Do ponto de vista metodológico, propomos a cartografia em um esforço de traçar linhas percorridas pelos bebês e sobre as quais se movimentam. Buscamos também evidenciar as forças as quais buscam atuar sobre eles. Trata-se de um ensaio teórico-conceitual que se produz na intersecção entre a pedagogia, as epistemologias da diferença e a sociologia da infância no sentido de contribuir para a educação e os estudos de bebês na direção da multidão e da multiplicidade.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0150.024
Scholarly communication0.0130.013
Open science0.0010.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0160.003

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 head0.105
GPT teacher head0.421
Teacher spread0.316 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2021
Admission routes1
Has abstractyes

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