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Record W3128184667 · doi:10.9771/gmed.v12i3.31879

Em defesa do realismo no ensino de geografia

2021· article· pt· W3128184667 on OpenAlexaff
Rafael Rossi

Bibliographic record

VenueGerminal Marxismo e Educação em Debate · 2021
Typearticle
Languagept
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsPhilosophyHumanities

Abstract

fetched live from OpenAlex

O presente texto aborda as contribuições da perspectiva ontológica e da defesa do realismo no ensino de Geografia a partir das contribuições da Pedagogia Histórico-Crítica e as elaborações do filósofo húngaro Lukács. Trata-se, desse modo, de compreender, num primeiro momento a reciprocidade dialética entre espaço e formação social. Num segundo momento, explicitamos o sentido de realismo, na apreensão mútua do movimento objetivo entre essência e aparência, tendo como base a perspectiva ontológica. Dessa forma, como conclusões, entendemos que no ensino de Geografia é preciso levar em conta que esta ciência e a educação não se explicam por si mesmas, mas nas interações que estabelecem com a sociedade como um todo. Compreende-se que a realidade deve ser apreendida em suas tendências essenciais e nas manifestações concretas e espaciais, para além das descrições enciclopédicas que não avançam sobre superficialidade e, ao mesmo tempo, para além dos posicionamentos idealistas que tentam exigir das objetividades possibilidades que não são reais.

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)0.005
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.049
Scholarly communication0.0120.013
Open science0.0020.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.247
Teacher spread0.237 · 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
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
Published2021
Admission routes1
Has abstractyes

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