Europeanization as Pragmatic Politics: Italy’s Civil Society Actors Operating in the Face of Right-Wing Populism
Bibliographic record
Abstract
This article examines how and under what conditions Italy’s civil society organizations (CSOs) have resorted to transnational activism and to what extent these efforts translate into impactful political advocacy. The analysis focuses on the action strategies of these civil society actors that have come under considerable pressure through the resurgence of populist–nationalist actors in the domestic arena. Developing an actor-centred perspective from below, this article draws on a series of 27 interviews conducted with these organizations’ representatives working primarily on issues related to migration and refugees in Italy. The empirical study examines some key initiatives that see domestic CSOs as protagonists in the transnational realm and explicates their motivations, approaches, and experiences. Conceptually, the article distinguishes between the vertical and horizontal Europeanization of CSOs. While there are notable opportunities for CSOs to engage in Brussels-centred governance and policy making, the effectiveness of horizontal Europeanization in the form of cross-border networking is—at first sight paradoxically—limited by the EU’s system of multi-level governance. The central argument about Europeanizing civil society activism is that these processes are primarily driven by a pragmatic pursuit of solutions to concrete political challenges that could not be properly addressed in an increasingly hostile domestic environment.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.036 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".