Behind the trigger: democracy, neoliberalism, and civilian militarism in Latin America
Bibliographic record
Abstract
The relationship between liberalism and militarism continues to spark debate, especially regarding the impact of neoliberalism. While militarism is often seen as a threat to democracy, it can paradoxically enhance state capacity when strategically employed within radical political projects. This paper presents a comparative analysis of Argentina, Costa Rica, Venezuela and Colombia from 1982 to 2004, examining the interplay of political, military and economic networks of power. Using the concept of ‘civilian militarism’, this study reveals how neoliberal adjustments allowed the rise of civilian authorities that promoted militaristic values, using military actions and norms to pursue political goals in response to crises. It explores how neoliberal policies and transformations, sometimes compounded by contradictions surrounding the illegalisation of hard drugs, opened space for the emergence of radical political projects. This deterioration, coupled with weak political or civil society activism allowed militaristic leaders to rise with the intention of addressing the troubled times in some countries more than others. By offering a macro-historical comparative perspective, this paper demonstrates how neoliberalism, and the limitations of civilian and political actors, in some countries pave the way for the emergence of civilian militarism, which, if not contained, can lead to authoritarianism.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".