A Gestalt perspective on Manichaean worldviews and individuals’ engagement in violence: the case of the Italian far left
Why this work is in the frame
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Bibliographic record
Abstract
Besides socio-political and economic factors, extant research contends that Manichaean worldviews, characterized by mutually exclusive dichotomies such as ‘good-bad’, are the main driver influencing individuals’ decision to use violence against others. Furthermore, extant scholarship identifies ideologies, populism, and conspiracy theories as the three originators of Manichaean worldviews. However, the findings from my research, carried out between 2018 and 2023, challenge these arguments. Using narrative analysis, this article examines personal stories of a group of Italian former far-left militants, who participated in the violent campaign of the so-called ‘Years of Lead’. Far-left and far-right ideologies strongly influenced Italian socio-political movements of the time. Thus, this paper explores whether Manichaean perspectives informing far-left militants’ decision to resort to violence originated from far-left ideologies or whether they existed independently of these ideologies. I develop this analysis through the lens of Gestalt psychology, which considers human behavior as resulting from how our minds understand the relation between components of our surrounding environment. While confirming relations between Manichaean worldviews and violence, this paper finds that Manichaean perspectives result from human cognitive processes and are then rigidified by ideological narratives. This work provides important insight to better understand radicalization and engagement in violence, and to develop appropriate responses to prevent it.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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