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- ItemMachine learning for policing: a case study on arrests in Chile(2020) Wout, Elwin van't; Pieringer Baeza, Christian Philip; Torres Irribarra, David; Asahi Kodama, Kenzo Javier; Larroulet Philippi, Pilar; CEDEUS (Chile)Police agencies expend considerable effort to anticipate future incidences of criminal behaviour. Since a large proportion of crimes are committed by a small group of individuals, preventive measures are often targeted on prolific offenders. There is a long-standing expectation that new technologies can improve the accurate identification of crime patterns. Here, we explore big data technology and design a machine learning algorithm for forecasting repeated arrests. The forecasts are based on administrative data provided by the national Chilean police agencies, including a history of arrests in Santiago de Chile and personal metadata such as gender and age. Excellent algorithmic performance was achieved with various supervised machine learning techniques. Still, there are many challenges regarding the design of the mathematical model, and its eventual incorporation into predictive policing will depend upon better insights into the effectiveness and ethics of preemptive strategies.
- ItemWork Status, Financial Stress, Family Problems, and Gender Differences in the Prevalence of Depression in Chile(Oxford University Press, 2019) González Medina, Gabriel; Vives Vergara, Alejandra; CEDEUS (Chile)Introduction: It is widely known that women have a higher prevalence of depression than men. These differences may be explained by social differences between women and men due to gender roles. In Chile, as elsewhere, women have greater household responsibilities, lower job incomes, and especially low labor market participation. However, the incidence of these gender differences on the higher prevalence of depression in women requires further study in the Chilean context. Objective: To identify main social differences between women and men associated with gender differences in the prevalence of depression in middle-aged Chilean men and women. Data source: Data comes from the second Chilean National Health Survey (2009-2010), a cross-sectional, nationally representative sample (n = 2771) composed of 1103 men and 1668 women (39.8 and 60.2%, respectively), whose age range goes from 25 to 55 years old. This study was approved by the Ethics Committee of Pontificia Universidad Catolica de Chile. Methods: Prevalence ratios were calculated through Poisson regression models to estimate associations between the prevalence of past episodes of depression and social stressful life events variables for men and women separately. Gender prevalence ratios of depression (Gender PR) adjusted for age and subsequently adjusted by the social and stressful life events variables. The analyses considered factors such as age, educational level, per-capita household income, work status, role as the head of household, marital status, events of violence, family problems, personal health problems or accidents, and self-reported financial stress. Results: This study finds that doing housework, reporting a serious family problem and having high financial stress were associated with a higher prevalence of depression in both genders. Whereas, health problems were only associated with prevalence in men. The age-adjusted gender PR was 2.84 [confidence interval (CI): 2.0-4.1], and when all selected variables were included attenuated to a PR of 1.86 (CI 1.3-2.7). The variable most strongly associated with depression in the fully-adjusted model was housework (PR: 5.3; CI: 1.3-21.0). Conclusion: In conclusion, this study finds that depression in in Chile is associated with social factors such as participation in housework, family problems, and financial stress, all of which are more common in women. To make further progress in the study of this public health problem in Chile, it is essential to incorporate more detailed characterization of gender roles in surveys and other studies. Likewise, social policies and interventions that contribute to reduce gender social inequalities in the exposure to adverse life circumstances can contribute to reduce unnecessary and avoidable gender disparities in health.