Higher Education as a Promoter of Soft Skills in a Sustainable Society 5.0
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The growing digitalization that is taking place in most current societies, shaping a super-smart society – such as, for example, the aimed Society 5.0 – raises profound implications in the learning that the higher education context should foster, and which is summarized in the following question: what kind of skills should be taught and how? This perspective paper aims to analyze the centrality of soft skills in this new and unavoidable context, as well as the implications in the learning process. The results of a bibliographical search point toward the fact that, in addition to professional and scientific skills, soft skills are critical for professional and personal success, which implies a profound reformulation of the teaching processes in the overwhelming majority of higher education institutions and their actors. For this challenge to become a reality and for the success of these processes, elements such as digital literacy, sustainability and interculturality are paramount.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it