Policy as a struggle for meaning: disentangling knowledge translation across international health contexts

Over the last decade, research in medical science has focused on knowledge translation and diffusion of best practices to enable improved health outcomes. However, there has been less attention given to the role of policy in influencing the translation of best practice across different national contexts. This paper argues that the underlying set of public discourses of healthcare policy significantly influences its development with implications for the dissemination of best practices. Our research uses Critical Discourse Analysis to examine the policy discourses surrounding the treatment of stroke across Canada and the U.K. It focuses in specific on how concepts of knowledge translation, user empowerment, and service innovation construct different accounts of the health service in the two countries. These findings provide an important yet overlooked starting point for understanding the role of policy development in knowledge transfer and the translation of science into health practice. © 2011 Operational Research Society. All rights reserved.

The impact of government policy on technology transfer: An aircraft industry case study

This case study explores the interaction between domestic and foreign governmental policy on technology transfer with the goal of exploring the long-term impacts of technology transfer. Specifically, the impact of successive licensing of fighter aircraft manufacturing and design to Japan in the development of Japan's aircraft industry is reviewed. Results indicate Japan has built a domestic aircraft industry through sequential learning with foreign technology transfers from the United States, and design and production on domestic fighter aircraft. This process was facilitated by governmental policies in both Japan and the United States. Published by Elsevier B.V.

Simulating early adoption of alternative fuel vehicles for sustainability

We quantify the conditions that might trigger wide spread adoption of alternative fuel vehicles (AFVs) to support energy policy. Empirical review shows that early adopters are heterogeneous motivated by financial benefits, environmental appeal, new technology, and vehicle reliability. A probabilistic Monte Carlo simulation model is used to assess consumer heterogeneity for early and mass market adopters. For early adopters full battery electric vehicles (BEVs) are competitive but unable to surpass diesels or hybrids due to purchase price premium and lack of charging availability. For mass adoption, simulations indicate that if the purchase price premium of a BEV closes to within 20% of an in-class internal combustion engine (ICE) vehicle, combined with a 60% increase in refuelling availability relative to the incumbent system, BEVs become competitive. But this depends on a mass market that values the fuel economy and CO2 reduction benefits associated with BEVs. We also find that the largest influence on early adoption is financial benefit rather than pro-environmental behaviour suggesting that AFVs should be marketed by appealing to economic benefits combined with pro-environmental behaviour to motivate adoption. Monte Carlo simulations combined with scenarios can give insight into diffusion dynamics for other energy demand-side technologies. © 2012 Elsevier Inc.

Code-specific policy gradient rules for spiking neurons

Although it is widely believed that reinforcement learning is a suitable tool for describing behavioral learning, the mechanisms by which it can be implemented in networks of spiking neurons are not fully understood. Here, we show that different learning rules emerge from a policy gradient approach depending on which features of the spike trains are assumed to influence the reward signals, i.e., depending on which neural code is in effect. We use the framework of Williams (1992) to derive learning rules for arbitrary neural codes. For illustration, we present policy-gradient rules for three different example codes - a spike count code, a spike timing code and the most general "full spike train" code - and test them on simple model problems. In addition to classical synaptic learning, we derive learning rules for intrinsic parameters that control the excitability of the neuron. The spike count learning rule has structural similarities with established Bienenstock-Cooper-Munro rules. If the distribution of the relevant spike train features belongs to the natural exponential family, the learning rules have a characteristic shape that raises interesting prediction problems.

On-line policy optimisation of Bayesian spoken dialogue systems via human interaction

A partially observable Markov decision process has been proposed as a dialogue model that enables robustness to speech recognition errors and automatic policy optimisation using reinforcement learning (RL). However, conventional RL algorithms require a very large number of dialogues, necessitating a user simulator. Recently, Gaussian processes have been shown to substantially speed up the optimisation, making it possible to learn directly from interaction with human users. However, early studies have been limited to very low dimensional spaces and the learning has exhibited convergence problems. Here we investigate learning from human interaction using the Bayesian Update of Dialogue State system. This dynamic Bayesian network based system has an optimisation space covering more than one hundred features, allowing a wide range of behaviours to be learned. Using an improved policy model and a more robust reward function, we show that stable learning can be achieved that significantly outperforms a simulator trained policy. © 2013 IEEE.

City versus national energy use: implications for urban energy policy and strategies

The global trend towards urbanization means that over half of the world's population now lives in cities. Cities use energy in different proportions to national energy use averages, typically corresponding to whether a country is industrialized or developing. Cities in industrialized countries tend to use less energy per capita than the national average while cities in developing countries use more. This paper looks at existing World Bank data in respect to urban energy consumption, the emissions inventory work done by New York City, and discusses how this data highlights the need for a focus on: energy policy for buildings in industrialized cities; masterplanning and new construction standards in developing cities; and how urban energy policy can become more effective in reducing urban greenhouse gas emissions.

Statistical analysis of microscale gas flows and stock price changes

First, recent studies on the information preservation (IP) method, a particle approach for low-speed micro-scale gas flows, are reviewed. The IP method was validated for benchmark issues such as Couette, Poiseuille and Rayleigh flows, compared well with measured data for typical internal flows through micro-channels and external flows past micro flat plates, and combined with the Navier-Stokes equations to be a hybrid scheme for subsonic, rarefied gas flows. Second, the focus is moved to the microscopic characteristic of China stock market, particularly the price correlation between stock deals. A very interesting phenomenon was found that showed a reverse transition behaviour between two neighbouring price changes. This behaviour significantly differs from the transition rules for atomic and molecular energy levels, and it is very helpful to understand the essential difference between stock markets and nature.

The temporal and spatial evaluation on China's agricultural policy output since 1978

Since reform and opening up, how much contribution has China's implementation of new agricultural policy made to agricultural output? This paper is trying to establish an agricultural policy output econometric model for doing a quantitative analysis of China's new agricultural policy. The results show that China's agricultural policies on agricultural output have an average contribution rate of about 7% since 1978, which is consistent with the OECD's basic forecast. There are obvious temporal and spatial differences. Generally speaking, we can divide the contribution of agricultural policy into three periods, which are the start-up phase from 1978 to 1991 (14 years), the stationary phase from 1992 to 2002 (11 years) and the rising phase from 2003 to 2008 (6 years). In space, the contribution of agricultural policy underwent a process from the all-low in the start-up phase, the gradual increase in the stationary phase to the all-high in the rising phase. Northern and western regions are more sensitive to policies. There are three major factors that can affect the contribution of regional agricultural policies, which are the process of national industrialization strategy, terrain and the level of local finance.

公共政策制定程序对政策可接受性的影响

This research addresses the problems of public policy-making procedures. In conducting our research, we considered public policy as the allocation or reallocation of interests or resources among different members of the public. Due to limited resources, administrations should trade off all interests among different segments of society when formulating a policy. Unfortunately, in recent years there have been several mass conflicts with administration of public policy. This infers that some people’s interests were ignored or harmed by certain policies. According to the theory of procedural justice, people may accept the unexpected result if they consider the procedure is just. This research hypothesizes that there are certain problems in current policy-making procedures and that improving these procedures may make policies more acceptable. A pilot study was conducted by interviewing ten scholars from a range of disciplines. The interview record transcripts were coded by three analysts. The results indicate that: 1) Most of the scholars criticized current public policies as lacking sensitivity to public issues; 2) Most of them considered that current public policies do not resolve problems effectively; and 3) They all considered that psychology research may enhance awareness of public issues and improve the effectiveness of policy. In study 2, the procedure of public policy was tracked and compared with a social survey. The Beijing government would like to increase the taxi fare rate to cope with the rising price of petroleum. Although the majority of delegates in a hearing of witnesses supported the policy consideration, the social survey of 186 residents and 63 taxi drivers indicated that both of them oppose the consideration. The findings indicate that the hearing of witnesses was not able to delegate the opinions of the public, resulting in the policy failing to resolve the problem. Study 3 was a nonequivalent control group quasi-experiment. Visitors of two Internet Website were chosen as subjects for original photo games. For the experiment group, visitors were invited to express their desires and suggestions on the game rules for one week, and then declare rules referencing the suggestions before starting the game. Meanwhile, the control group simply declared the rules at the beginning of the game. Compared with the two games during 23 days, the experiment group submitted more photos than the control group. The results of this research imply that, the good will of policy makers is not enough to make a policy effective. Surveys on public attitudes at the beginning of the policy-making process can allow policy makers to better determine public issues, assess the tradeoff of public interests, help ensure policies are more acceptable, and help foster a harmonious society. The authors of this research suggest that psychology research should take more social level problems into account in the policy-making process.