Do Amoral Familism and Political Distrust Really Affect North–South Differences in Italy?
Bibliographic record
Abstract
Especially in southern Italy, Banfield’s amoral familism is considered an obstacle to the formation of associations and growth of political participation. This article discusses Banfield’s concept, showing that it has been vulgarized merely as familism and, in particular, demonstrates that Banfield intended amoral familism to be understood in terms of political distrust. We investigated whether amoral familism or political distrust, operationalized as an individual difference variable, mediated the relationships between personality traits, personal values, and conventional and unconventional political acts, controlling for differences in political attitude. We recruited 405 participants, distributed across north, central, and southern Italy, to complete a questionnaire on political participation that also assessed Big Five personality factors, values, sociability and political attitude (expertise, interest, self-efficacy), and a new scale assessing amoral familism as a form of political distrust. Regression analyses were used to identify the best predictors of political acts, then structural equation modeling was used to test a model of political participation. Like political attitudes, familism mediated the relationships between personality traits, especially “openness to experience” and “taking conventional and unconventional political acts.” However, our data do not confirm the stereotype that northern and southern Italians differ in their tendency to amoral familism as defined by Banfield.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".