Redes de políticas en el marco de la Agenda Urbana para la UE. La influencia de las coaliciones temáticas en la politización de la toma de decisiones a escala europea
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
This article explores the role of multilevel thematic partnerships method in building a specific policy, namely, the Urban Agenda for the European Union (EU) adopted in 2016. This method, designed as a pilot experiment, formalizes cooperation among different levels of government as well as public and private actors. The purpose of this paper is to examine the implementation of the multilevel governance approach and to determine the extent to which the thematic partnerships method contributes to the politicization of a decision-making process at the European level. For this purpose, the methodological design is based on network analysis applied to four case studies, namely, the following four thematic partnerships: Inclusion of Migrants and Refugees, Urban Poverty, Climate Action and Security in Public Spaces. Firstly, the results show a higher mobilization of stakeholders representing local interests; secondly, it is also shown that the monetization of the problem determines the nature of stakeholders (stakeholders representing social or economic interests) that join the policy networks. In sum, this article makes an empirical contribution to multilevel governance and politicization studies on the one hand, and to urban and European studies on the other.
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.
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 | 0.022 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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