Gangs as states and firms: Criminal organisations, smuggling markets and violence on Brazil’s frontiers.
Notice bibliographique
Résumé
Large criminal groups are often thought of as distinctive entities with their own rationales, specialised governance arrangements, and an inherent tendency to use indiscriminate violence.Arguably, criminal organisations instead behave very much like states and legal firms.They behave like states in their preoccupation with borders, dedicating attention and investment to some areas while not others, and they behave like firms by expanding to capture market share and vertically integrating in response to changes in their market environment.They make decisions based on locale-specific and market-specific costbenefit assessments and on the conditions imposed on them by exogenous shocks.In this dissertation, I argue that the frequently referenced "border effect" on criminal violence does not hold in Brazil, the country with the longest border in the whole American continent.Instead, hotspots central to organised criminal operations drive overall border violence.In addition, criminal governance takeovers can be understood as the product of a vertical integration, a process that, given the local context, can made perfect "corporate" sense.Also, I consider the internal logic of the so-called "balloon" and "cockroach" effects, showing them to be more than simple metaphors to describe the ineffectiveness of anti-crime initiatives.These effects can be instigated by states but also criminal groups and combine into chain reactions whereby the original shocks that trigger them lead to unintended consequences.Based on these results, I identify significant linkages that emerge between border hot spots, vertical integration by criminal organisations, and the knock-on effects that result from exogenous shocks to criminal organisations' operations.I call for a more pragmatic approach to examining criminal organisations: instead of thinking of them as distinctive entities with characteristics that set them apart from others, they behave to a large extent like "rational" firms and states that make informed decisions based on their local environments and the iii resources at hand.The importance of understanding the local-level conditions of criminal markets cannot be understated as they are crucial to identify the capacity or incentives of groups to effectively govern their competition with competing claimants to resources which, when lacking, often leads to violence.First and foremost, I would like to thank my supervisor, Jean Daudelin, who has been steadfast in his support for me throughout this dissertation.Thank you for your time, guidance, and especially your patience through the good and the bad.Without you I would not have discovered the world that is Brazil's borderlands.I am truly grateful.I also want to thank Dane Rowlands and John Sidel, my two
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,006 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,000 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».