MétaCan
Menu
Back to cohort
Record W4321384485 · doi:10.1590/1983-80422022304566es

Recursos del cine y enseñanza de la bioética en las ciencias del movimiento humano

2022· article· es· W4321384485 on OpenAlexaff
Luciana Teixeira Waltrick, Fernando Hellmann, Gelcemar Oliveira Farias, Alcyane Marinho

Bibliographic record

VenueRevista Bioética · 2022
Typearticle
Languagees
FieldHealth Professions
TopicFilm in Education and Therapy
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Resumen Este estudio descriptivo y exploratorio, realizado con egresados del Programa de Posgrado en Ciencias del Movimiento Humano de la Universidad do Estado de Santa Catarina, pretende conocer las ventajas de utilizar películas en la enseñanza de la bioética e identificar obras cinematográficas relacionadas con actividad física y salud en las ciencias del movimiento humano. Se utilizaron entrevistas semiestructuradas, y se aplicó el análisis de contenido a los datos. Las categorías a priori partieron de los objetivos, y las respuestas de los participantes generaron subcategorías a posteriori: Aportes del aprendizaje de la bioética para el Programa de Posgrado en Ciencias del Movimiento Humano y la vida profesional; y el uso del cine como recurso pedagógico, con sugerencias de películas y temas específicos. Los recursos del cine promueven un aprendizaje más significativo y placentero al posibilitar una aproximación de los estudiantes a los contenidos bioéticos de la profesión, facilitando el aprendizaje.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0050.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.033
GPT teacher head0.409
Teacher spread0.376 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueRevista BioéticaSame topicFilm in Education and TherapyFrench-language works237,207