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Record W6981320151

Educando en igualdad

2018· dissertation· es· W6981320151 on OpenAlexaboutno aff

Bibliographic record

VenueZaguan (Universidad de Zaragoza) · 2018
Typedissertation
Languagees
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Order (exchange)Field (mathematics)Quarter (Canadian coin)Power (physics)
DOInot available

Abstract

fetched live from OpenAlex

Este Trabajo de Fin de Grado trata de conocer las actitudes de los alumnos y las alumnas en materia de igualdad. Tras una exhaustiva revisión bibliográfica sobre la igualdad de género, se analizan a través del cuestionario Escala de Actitudes del alumnado hacia la Coeducación (García, Rebollo, Buzón, González, Barragán y Ruiz, 2010), las actitudes sexistas de un grupo de alumnos de 4º de primaria. A pesar de que los resultados diagnostican el tipo de actitudes que presentan estos alumnos, la muestra no es lo suficientemente representativa para extrapolar conclusiones hacia la población general, por lo que se aboga por diseñar un programa preventivo para educar en igualdad, destinado a los alumnos de segundo ciclo de educación primaria.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.002

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 head0.005
GPT teacher head0.246
Teacher spread0.241 · 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 designTheoretical or conceptual
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
Published2018
Admission routes1
Has abstractyes

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