Las competencias holísticas relacionadas al entorno empresarial y académico desde la Visión Salesiana
Bibliographic record
Abstract
El mundo actual se encuentra impulsado por el conocimiento, donde el ritmo del cambio es vertiginoso debido en gran medida a la tecnología que interviene directamente dando ventaja a las diferentes organizaciones (Khamdun et al., 2021). En esta línea, el desarrollo de la tecnología es posible por la intervención del ser humano y sus habilidades para transformarla, pero es indudable que existen habilidades interpersonales que apoyan estos procesos, y son conocidas como “competencias holísticas (Chan y Luk, 2022), “habilidades blandas”, “habilidades del siglo XXI”, “habilidades para la empleabilidad” (Barrie, 2006). Estas son cada vez más importantes y críticas para el éxito de cualquier profesión (Caeiro et al., 2021; Mulcahy et al., 2018; Olo et al., 2021; Sharvari y Kulkarni, 2019). Dado que el objetivo del presente estudio no es distinguir diferentes conceptualizaciones, se acuñará el término “competencias holísticas”.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.013 |
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; both teacher heads agree on what is shown here.
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".