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Record W7020321536

La adaptación ideológica como estrategia de dominio en las alianzas entre partidos competidores en la Comunitat Valenciana

2025· article· es· W7020321536 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2025
Typearticle
Languagees
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDomain (mathematical analysis)Border SecurityQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Este artículo adapta las teorías de la competición partidista a las dinámicas de las alianzas entre partidos políticos, considerando la ideología como un elemento contingente que puede ser instrumentalizado por estos para alcanzar sus objetivos. A partir de estas teorías, se plantea que, en las alianzas entre partidos competidores, el partido más grande puede adaptar su ideología a la del pequeño para tratar dominar y apropiarse de su territorio de caza. Para ello, se analizan tres alianzas de este tipo en la Comunitat Valenciana: Unió Valenciana y el Partido Popular de la Comunidad Valenciana, Unitat del Poble Valencià y el Partit Valencià Nacionalista, y el Bloc Nacionalista Valencià e Iniciativa del Poble Valencià (Compromís). El análisis confirma la expectativa inicial, aunque se deducen diferentes factores que influyen en esta. Primero, el grado de desigualdad entre los aliados condiciona la forma del dominio del partido grande y la evolución de la alianza. Segundo, que la existencia de una dimensión territorial compleja en la Comunitat Valenciana favorece la adaptación ideológica de los aliados. Además, se concluye que, incluso si en la alianza se genera una nueva identidad, como en el caso de Compromís, el partido más grande puede adaptarse a esta y tratar de neutralizar a su aliado.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.008
GPT teacher head0.282
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes1
Has abstractyes

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