The future of Spanish public Universities: The challenges of the excellence debate
Bibliographic record
Abstract
The aim of this study is to analyze the challenges facing Spanish public universities at a crucial moment for defining their essence. The political, economic, and social circumstances of the current moment oblige us to reflect on the role that universities should play today. This reflection will be essential in responding to the ever more exacting demands of market economies, the kinds of societies in which they are immersed. So, this paper tries to analyse the repercussions that global changes in politics and economics are having on public universities in Spain. Once again, we shall discover how globalization processes determine the education planning of a country. On this point, the compass of governance has set the course of the educational institutions for economic efficiency, following a set of market criteria which involve their own funding and results. Recently a report was made public by the Panel of Experts for the Reform of the Spanish University System, who were designated by the Minister of Education, Culture and Sports, José Ignacio Wert. This document invites social debate on the role of higher education institutions, at the same time that it poses the need for undertaking a series of unavoidable transformations affecting all university spheres and that are marked by the path of academic excellence and international competition.http://dx.doi.org/10.15572/ENCO2015.10
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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 | 0.027 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.031 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".