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Record W2943608049 · doi:10.15517/revedu.v43i1.28509

Representaciones en torno a la elección de la docencia desde el discurso de las familias y el estudiantado de Pedagogía

2019· article· es· W2943608049 on OpenAlexaff
Héctor Gómez

Bibliographic record

VenueRevista Educación · 2019
Typearticle
Languagees
FieldSocial Sciences
TopicEducational Practices and Policies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHumanitiesArtSociology

Abstract

fetched live from OpenAlex

El presente artículo tiene como objetivo comprender las representaciones discursivas de las familias y de sus hijos e hijas, ante la elección de la docencia en estudiantes de Pedagogía en Educación Básica de una universidad con baja selectividad[1]. El estudio de carácter mixto, utiliza dos encuestas y dos estudios de caso, analizados de forma secuencial y triangulada, revelan que no existe relación directa entre elección de la carrera y el estatus de esta; el apoyo tanto familiar como del entorno en la elección docente si bien aparece con ciertas aprehensiones al comienzo, se incrementa a medida que el estudiantado avanza en su formación; en cuanto a la influencia, la figura docente aparece con un alto protagonismo, más aún cuando es integrante de la familia. Asimismo, la elección estaría fuertemente vinculada al compromiso social y vocación por enseñar. [1] Se entiende por universidad de baja selectividad aquellas instituciones que, de acuerdo con Rufinelli (2014), promediaron entre 450 puntos y 549 en la Prueba de Selección Universitaria. Cabe señalar que las puntuaciones finales varían entre 150 a 850 puntos.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0080.007
Scholarly communication0.0080.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.014
GPT teacher head0.406
Teacher spread0.392 · 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 designQualitative
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

Citations5
Published2019
Admission routes1
Has abstractyes

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