Capacidad estatal en el control de actividades criminales: las dinámicas de corrupción en el control de los teléfonos móviles en establecimientos penitenciarios de Lima Metropolitana

La presente investigación aborda los límites en las capacidades estatales derivados de las prácticas de corrupción. Para ello, se toma como caso de estudio las prácticas de corrupción en el control del ingreso y del uso de teléfonos celulares en establecimientos penitenciarios de Lima Metropolitana durante el periodo comprendido entre los años 2011 y 2016, y su objetivo es comprender cómo se han implementado dichas medidas. A partir de ello, se proponen tres objetivos específicos: primero, se busca describir las dinámicas de ingreso y uso de los teléfonos móviles en los establecimientos penitenciarios de Lurigancho y Miguel Castro Castro. Segundo, se busca determinar las prácticas de corrupción asociadas a las medidas de control del ingreso y uso de los teléfonos móviles y su efecto sobre la implementación de las mismas. Tercero, se busca explicar los límites de dichas medidas de control ante el fenómeno de la corrupción. De lo analizado, se tiene que la capacidad de un organismo estatal puede verse mermada no solo por la insuficiencia de recursos o cobertura de sus funciones, sino también por la existencia de dinámicas de pequeña o “micro corrupción”, que están asociadas a vulnerabilidades en las medidas de control de ingreso y uso de teléfonos móviles, las cuales se explican debido a la falta de recursos para la implementación de la normativa existente y a la necesidad del mantenimiento del frágil equilibrio existente en estos espacios. Asimismo, estas dinámicas continúan reproduciéndose debido a que dichas medidas de control tienen un impacto limitado, pues solo apelan a la concientización de los involucrados sobre el problema (campaña contra la corrupción, incentivos simbólicos, etc.), menguando así la eficiencia para ejercer un control efectivo por parte del Estado.This research addresses the limits on state capacity derived from corrupt practices. Therefore, it is taken as a case of study, the corruption practices in the control of entry and use of cell phones in penitentiary establishments of Lima, during the period between the years 2011 and 2016, and its objective is to understand how such measures have been implemented. Based on this, three specific objectives are proposed: first, the aim is to describe the dynamics of entry and use of cell phones in the penitentiary establishments of Lurigancho and Miguel Castro Castro. Second, it seeks to determine the practices of corruption associated with control measures regarding the entry and use of cell phones and their effect on the their implementation. Third, it seeks to explain the limits of those control measures against corruption practices. Thus, the capacity of a state agency can be reduced not only by insufficient resources or coverage of its functions, but also by the existence of small or "micro-corruption" dynamics, which are associated with vulnerabilities in control measures of entry and use of cell phones, which are explained due to the lack of resources for the implementation of the existing regulations and the need to maintain the fragile balance in these spaces. In addition, these dynamics continue to be reproduced because the control measures have a limited impact, since they only appeal to awareness of those involved in the problem (anti-corruption campaign, symbolic incentives, etc.); hence, the efficiency to exercise control by the State is reduced.Tesi

A global analysis of the impact of COVID-19 stay-at-home restrictions on crime

The implementation of COVID-19 stay-at-home policies was associated with a considerable drop in urban crime in 27 cities across 23 countries. More stringent restrictions over movement in public space were predictive of larger declines in crime. The stay-at-home restrictions to control the spread of COVID-19 led to unparalleled sudden change in daily life, but it is unclear how they affected urban crime globally. We collected data on daily counts of crime in 27 cities across 23 countries in the Americas, Europe, the Middle East and Asia. We conducted interrupted time series analyses to assess the impact of stay-at-home restrictions on different types of crime in each city. Our findings show that the stay-at-home policies were associated with a considerable drop in urban crime, but with substantial variation across cities and types of crime. Meta-regression results showed that more stringent restrictions over movement in public space were predictive of larger declines in crime.Peer reviewe

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

A global analysis of the impact of COVID-19 stay-at-home restrictions on crime

The stay-at-home restrictions to control the spread of COVID-19 led to unparalleled sudden change in daily life, but it is unclear how they affected urban crime globally. We collected data on daily counts of crime in 27 cities across 23 countries in the Americas, Europe, the Middle East and Asia. We conducted interrupted time series analyses to assess the impact of stay-at-home restrictions on different types of crime in each city. Our findings show that the stay-at-home policies were associated with a considerable drop in urban crime, but with substantial variation across cities and types of crime. Meta-regression results showed that more stringent restrictions over movement in public space were predictive of larger declines in crime