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Record W2460177485 · doi:10.5539/ass.v12n8p11

Student Participation in the Governing Bodies of Spanish Universities

2016· article· en· W2460177485 on OpenAlexvenueno aff
Mercedes Llorent Vaquero

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Teaching and Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsExpeditingDemocracyStatuteQuality (philosophy)Political scienceSample (material)Class (philosophy)Space (punctuation)Mathematics educationSociologyPublic administrationPsychologyLawPoliticsManagementEconomicsComputer scienceEpistemology

Abstract

fetched live from OpenAlex

<p class="a"><span lang="EN-GB">Spanish universities are making considerable democratic efforts in their various governing and administrative bodies. This article analyses the role that students play in these in aiding the development of a society where democratic values prevail. To achieve this, documentary analysis is used to explore the different laws and statutes of the universities in terms of student participation, as well as the methodology characteristic of Comparative Education. The first phase tackles the problem of student participation in Spanish universities. Following this, student participation in these bodies is analysed, observing differences and similarities taken from a sample of different Spanish universities. Based on the results obtained, student participation does not quite reach the levels desired. Once the problem is identified a series of proposals are made to increase the quantity and quality of this participation, most importantly increasing the relevance of the student sector in governing bodies, expediting and simplifying electoral processes, supporting the right to association by creating space and providing the necessary training for students to make full use of their rights. </span></p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.417
Teacher spread0.375 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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