Economía social y solidaria en la educación superior: un espacio para la innovación (Tomo 1)
Bibliographic record
Abstract
This first volume of the collection Social and Solidarity Economy in Higher Education: a space for innovation is made up of articles that account for the powerful link that is generated by introducing the reality, theory, and practice of the social and solidarity economy in the curriculum of universities in the United Kingdom, Colombia, Argentina, Canada, France, Spain, and Brazil. The authors present experiences that contribute to the improvement of institutional pedagogical models, to the development of competences for teachers and to the empowerment of young people from the classroom to influence their local realities. This is done through examples of curricular developments that lead to the management of cooperatives and the promotion of public policies in alliance with national governments. Also, experiences of dialogue of knowledge are exposed and it is shown how the link with agroecological markets can be a scenario of social appropriation of knowledge that stimulates citizen participation. In the last chapters, the importance of university ecosystems supporting the social and solidarity economy and the experience of incubators to tune the academic community with the territory are highlighted. Thus, how this strategy allows proposing effective solutions to social, economic and environmental problems or needs is highlighted through solidarity entrepreneurship and social innovation. As in the other volumes, it is evident that the experience of education in social and solidarity economy can not only respond to the demands of a changing world, it can also inspire the appropriation of the future for the achievement of the global common good.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".