‘We the People’: Demarcating the Demos in Populist Mobilization—The Case of the Italian Lega
Bibliographic record
Abstract
This article is a theoretically guided and empirically based analysis of how populist movements invoke the notion of the ‘people’ as a cornerstone of their political mobilization. While the confrontation between the virtuous ‘people’ and the unresponsive elites speaks to how populism challenges established political actors and institutions, the actual meaning of who the ‘people’ are and what they represent is shifting and often driven by strategic considerations. Analytically the article investigates the distinct ways in which nationalism and populism conceptualize and politically mobilize the notion of the ‘people’. Empirically it focuses on the Italian League and engages in a discourse analysis of its political campaigns over the past 30 years. Based on this textual analysis of political campaigns, the article sheds light on how the reference to the ‘people’ has been employed as this political actor has transformed from a regionalist party advocating for autonomy in Northern Italy to one taking up the role of a populist-nationalist party at the national level. This case study allows the author to make a generalizable hypothesis about the nature of identity politics promoted by populist actors and the way in which the invocation of the ‘people’ and their alleged enemies is a pivotal political narrative that opens and restricts opportunities for political mobilization. This interpretative approach also allows for a more concise conceptual understanding of the affinity that right-wing populists demonstrate toward nativist ideologies.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.029 | 0.093 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".