Causes of Congestion in the Justice System. Does Macroeconomic Environment Matter?

Public services rendered by the justice system institutions are susceptible to congestion which arise from partial rivalry in consumption of these services. This paper investigated the causes of congestion in Kenyan justice system laying emphasis on select macroeconomic variables. A structural model was estimated using instrumental variable method, that entailed the use of data for the period 1960-2016. The findings were that increase in funding to justice system institutions, economic growth and enhanced resolution of cases reduces congestion. We recommend that the Government efforts to reduce congestion should cut across the demand and supply side of the justice market, and on environmental factors that affect the proper functioning of the justice sector. This should involve setting time limits, preferably through legislations, on the maximum period different types of cases should take to be finalized. Such a legislation could also specify the timelines that other players in the justice sector should take to finalize their legal tasks in relation to dispute resolution process. Further, allocation of optimal fiscal resources to justice system institutions would be crucial in financing congestion reduction programmes especially on uptake of technology and upgrading of capital infrastructure. Keywords: Congestion, Macroeconomic Variables, Cause

Evaluation of Penalty and Enforcement Strategies to Combat Speeding Offences among Professional Drivers: A Hong Kong Stated Preference Experiment

You are viewing a past publication from the Good Systems Network Digest in July 2020.Office of the VP for Researc

Describing/Modelling the Dynamics of Pedestrian Behaviour: From the Role of Ambiance to a Hypothesis for a Physical Model

Let us look a little closely at the movement of people in public space. What do we see if we follow their paths, the relations played out among them, the areas occupied or left empty and, more importantly, the dynamics of these constant variations and adjustments? In designing public space, it is increasingly important to look at potential movement. This is the case whether considering the quality and diversity of itineraries (e.g. through parks, museums, stadiums, squares) or for the ease with which the public can get in to or out of a given place (e.g. shopping centres and railway stations). We must therefore seek to understand both the individual and collective dynamics involved here and bring to bear analysis and design tools that take them into account. Pedestrian behaviour in public space is a vast subject of research, involving numerous disciplines. This article will address it from the point of view of path making. The approach developed here highlights the role played by architectural and urban surroundings (Jean-François Augoyard 1979) in pedestrian dynamics, as situations of sensory interaction, which we experience according to a network-actor system (Bruno Latour, 2006). The actor may be a physical person, a group of persons, a moveable or fixed built object or semiographic features within the space, sensory elements of the environment such as a particular light, a zone or source of heat or coolness, soothing or stress-inducing sounds, and so on. We will first present the adaptation of a method of observation in situ (recurrent observation, (Pascal Amphoux, 2001), then describe experiments with a numerical relational model. This is the physical model developed by ACROE, which generates dynamics using the descriptors and operators of Newtonian physics (the force concept and the principle of action-reaction). The initial subject of study is an element of public architecture that is particularly dynamic, namely the automatic double doors at the entrance to a shopping centre. Since this first study (Tixier, 2000 ), numerous applications of this model have been developed and have enabled an approach to the whole of urban configurations having to do with public space to take place with a view to analysing existing spaces and investigating spatial design. This is covered in the third section of this article

The medical pause in simulation training

The medical pause, stopping current performance for a short time for additional cognitive activities, can potentially advance patient safety and learning in medicine. Yet, to date, we do not have a theoretical understanding of why pausing skills should be taught as a professional skill, nor empirical evidence of how pausing affects performance and learning. To address this gap, this thesis investigates the effects of pausing in medical training theoretically and empirically. For the empirical investigation, a computer-based simulation was used for the task environment, and eye-tracking and log data to assess performance

Evaluation of Ontario\u27s Street Racers, Stunt and Aggressive Drivers Legislation

The purpose of this thesis was to conduct a process and outcome evaluation of the deterrent effect of Ontario’s Street Racers, Stunt and Aggressive Drivers Legislation. The focus of this study was on police enforcement (implementation), a change in speeding on the provincial highways (intermediate outcome) as well as on a decrease in both extreme speeding convictions and casualties, measured as a sum of injuries and fatalities (criterion outcomes). The deterrent effect of the legislation on Ontario drivers was examined, using data obtained from the Ministry of Transportation of Ontario. Employing interrupted time series analyses with ARIMA modelling, we found a significant reduction in both criterion outcome measures for the intervention group(s), comparing the series before and after the intervention. No corresponding changes were found for the comparison group(s). The findings suggest that the examined legal intervention was effective in deterring illegal risky driving behaviours and improving road safety

Explainable and Advisable Learning for Self-driving Vehicles

Deep neural perception and control networks are likely to be a key component of self-driving vehicles. These models need to be explainable - they should provide easy-to-interpret rationales for their behavior - so that passengers, insurance companies, law enforcement, developers, etc., can understand what triggered a particular behavior. Explanations may be triggered by the neural controller, namely introspective explanations, or informed by the neural controller's output, namely rationalizations. Our work has focused on the challenge of generating introspective explanations of deep models for self-driving vehicles. In Chapter 3, we begin by exploring the use of visual explanations. These explanations take the form of real-time highlighted regions of an image that causally influence the network's output (steering control). In the first stage, we use a visual attention model to train a convolution network end-to-end from images to steering angle. The attention model highlights image regions that potentially influence the network's output. Some of these are true influences, but some are spurious. We then apply a causal filtering step to determine which input regions actually influence the output. This produces more succinct visual explanations and more accurately exposes the network's behavior. In Chapter 4, we add an attention-based video-to-text model to produce textual explanations of model actions, e.g. "the car slows down because the road is wet". The attention maps of controller and explanation model are aligned so that explanations are grounded in the parts of the scene that mattered to the controller. We explore two approaches to attention alignment, strong- and weak-alignment. These explainable systems represent an externalization of tacit knowledge. The network's opaque reasoning is simplified to a situation-specific dependence on a visible object in the image. This makes them brittle and potentially unsafe in situations that do not match training data. In Chapter 5, we propose to address this issue by augmenting training data with natural language advice from a human. Advice includes guidance about what to do and where to attend. We present the first step toward advice-giving, where we train an end-to-end vehicle controller that accepts advice. The controller adapts the way it attends to the scene (visual attention) and the control (steering and speed). Further, in Chapter 6, we propose a new approach that learns vehicle control with the help of long-term (global) human advice. Specifically, our system learns to summarize its visual observations in natural language, predict an appropriate action response (e.g. "I see a pedestrian crossing, so I stop"), and predict the controls, accordingly

Inequality, Regional Economic Development and Access to Public Services in Decentralizing Indonesia

This thesis aims to answer what is happening to inequality in Indonesia for the past years. This empirical research consists of two parts, first, how is the relationship between inequality and development in Indonesia along with various aggregation levels; second, whether the accessibility to basic public services is the implication of inequality. The key messages of the first part of this thesis are as follows: over the last decades relatively high economic growth in Indonesia is associated with rapidly increasing income inequality. Regional convergence of inequality across islands and provinces is driven by the fact that incomes of the rich in poor regions grow faster than those of the poor in rich regions. In other words, the middle class and especially the top incomes seem to benefit most from the economic growth dynamics in Indonesia. In relation to urbanization, our examination shows that if the current trend of increasing average agglomeration size continues, we can expect that inequality will further go up. Further, high inequality in the past will increase the subsequent growth, this high growth is then associated with high inequality in the current period. If this current inequality is too high, then the change in inequality will be positive and large enough to reduce growth in the future. In other words, the impact of high inequality in the past is associated with the slowing down economic growth and worsening existing inequality. It seems that our results support the Piketty (2014) argument that inequality keeps increasing as societies accumulate wealth. With regards to the institutional quality, the type of institutional quality plays a significant role in shaping the association with economic growth in the future. This role looks more important if we interact with the initial inequality suggesting that a combination of a certain degree of inequality and institutional quality is required to boost the economic growth. The key messages of the second part of this thesis are as follows: given the health reform promoting inclusiveness in health access and given the complexity of connecting all people including from all the relatively small islands with huge disparities in terms of income and geography, insured people behave differently than uninsured people, and within the insured group, the subsidized people behave differently from the non-subsidized people. Ex ante moral hazard exists in insured and subsidized groups. The disparity in access to electricity and its supply is high across Indonesia. Despite the fact that electrification already started more than one hundred years ago, the electrification ratio remains low and the speed of technology diffusion is slow. Population density as an internal factor and power supply availability as an external factor contribute to increasing the electrification ratio at the province level. This external factor can be translated as island barrier. Hence, the heterogeneity at the province level contributes in shaping the diffusion patterns

The Inclusive Growth and Development Report 2017

Around the globe, leaders of governments and other stakeholder institutions enter 2017 facing a set of difficult and increasingly urgent questions:With fiscal space limited, interest rates near zero, and demographic trends unfavorable in many countries, does the world economy face a protracted period of relatively low growth? Will macroeconomics and demography determine the world economy's destiny for the foreseeable future?Can rising in-country inequality be satisfactorily redressed within the prevailing liberal international economic order? Can those who argue that modern capitalist economies face inherent limitations in this regard – that their internal "income distribution system" is broken and likely beyond repair – be proven wrong?As technological disruption accelerates in the Fourth Industrial Revolution, how can societies organize themselves better to respond to the potential employment and other distributional effects? Are expanded transfer payments the only or primary solution, or can market mechanisms be developed to widen social participation in new forms of economic value-creation?These questions beg the more fundamental one of whether a secular correction is required in the existing economic growth model in order to counteract secular stagnation and dispersion (chronic low growth and rising inequality). Does the mental map of how policymakers conceptualize and enable national economic performance need to be redrawn? Is there a structural way, beyond the temporary monetary and fiscal measures of recent years, to cut the Gordian knot of slow growth and rising inequality, to turn the current vicious cycle of stagnation and dispersion into a virtuous one in which greater social inclusion and stronger and more sustainable growth reinforce each other?This is precisely what government, business, and other leaders from every region have been calling for. Over the past several years, a worldwide consensus has emerged on the need for a more inclusive growth and development model; however, this consensus is mainly directional. Inclusive growth remains more a discussion topic than an action agenda. This Report seeks to help countries and the wider international community practice inclusive growth and development by offering a new policy framework and corresponding set of policy and performance indicators for this purpose