Prueba preliminar de una versión en español de la medida de participación grupal para avanzar en la práctica basada en evidencia en grupos
Bibliographic record
Abstract
Evidence-based practice in groups includes research-based measures to assess group processes and outcomes. However, there are few evidence-based, culturally relevant instruments that can assist professionals in delivering evidence-based groups in Spanish to increase participant’s engagement and retention. This paper describes a project to translate a reliable and valid English version of the Group Engagement Measure (GEM) into Spanish and its relevancy to improve research outcomes when implementing socio-educational interventions in communities with family participation. The process of translation was deliberate and methodical, which produced a Spanish version for empirical testing named Medida de Compromiso en Trabajo Grupal (GEM-27). The measure demonstrated high internal consistency, with a Cronbach’s alpha of .94, and a low standard error of measurement (3.74). As a part of evidence-based practice in groups, the Spanish GEM can help advance the measurement of important connections in the group, strengthening the helpfulness of group work in Spanish countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".