Realistic Policy Research Articles

At the End of Every Pandemic: Beginning a Pandemic Playbook to Respond to the Next.

The world was unprepared for COVID-19. Pandemics can unfold quickly; faster than governments can respond, unless they have maintained a realistic pandemic playbook. As the world ahead becomes ever-more complex, such playbook becomes ever-more necessary. This article not only describes the importance of a pandemic playbook but also a system to maintain it. A pandemic playbook both (1) specifies what is needed to respond to a pandemic and (2) provides a lens through which to identify measures that will keep people safe and society secure. The plays in the book are thought-though policies and strategies and corresponding implementation plans. The process of developing a playbook is as important as the product. Any playbook must be fit for purpose in the context of the times in which it is to be used. Above all, it must contain realistic policies and plans that can actually be implemented and can realize their intended effects. Achieving this goal requires (1) repeatedly exercising the playbook so that people know what to do when they need to do it and (2) evaluating results and updating the playbook to keep it relevant and current. Necessarily, to bring ideas alive, this article illustrates them with reference to COVID-19 and earlier pandemics, but it is not intended as a playbook for responding to the next pandemic; nor a postmortem on responses to COVID-19. Instead, it describes actions to take now to be ready when the next global pandemic strikes, so that policy decision-makers will not be lamenting “we should have done that.”

Varieties of Economic Vulnerability: Evidence on Social Policy Preferences and Labor Informality from Mexico

ABSTRACTIn many Latin American countries, social policy preferences among economically vulnerable citizens seem largely unpolarized. However, current studies rarely confront citizens with realistic policy options and often lack the required detail to capture the heterogeneity of economic vulnerability. Drawing on the dualization debate, we expect individuals facing different degrees of vulnerability to show distinct social policy preferences. Using original survey data from Mexico and a conjoint experiment, our findings reveal a complex divide, where the most economically vulnerable are least supportive of public solutions. Sharing the home with a formal labor market participant does not seem to mitigate social policy skepticism among the vulnerable. In contrast, magnified vulnerability via household composition reduces support for welfare policy expansion. Social policy preferences become much less distinct when policy design alternatives are introduced, suggesting reduced expectations about the state’s role and a lack of clarity about the tangible benefits of social policy reform.

Convergence in renewable energy consumption and their influencing factors across regions: evidence from convergence algorithm approach.

This study examines the convergence in renewable energy consumption over the period 2000-2018 by using a convergence algorithm developed by Phillips and Sul. We used 183 countries which were sub-divided into five regions, namely: Sub-Saharan Africa (SSA); Middle East and North Africa (MENA); Europe and Central Asia (ECA); East and South Asia and the Pacific (ESAP); and America. The possible influencing determinants of the convergence/divergence clubs for the regions were also investigated by utilising multinomial logit regression. The determinants were majorly classified into macroeconomic, socio-economic, and institutional quality variables, which were computed via principal component analysis by using six governance indicators. The results show an absence of panel convergence and a weak speed of convergence for the regions. The final club formation results obtained from the iteration procedure show that 6 clubs (for SSA), 2 (for MENA and ECA), 5 (for ESAP), and 3 (for America) were formed for the regions. The determinants of renewable energy consumption play both significant and insignificant roles in the likelihood of a country belonging to a particular convergence club in each of the regions. This study found that at the regional level, the process of convergence in renewable energy consumption is yet to echo desirable emanations of renewable energy consumption policies sharing similar characteristics, but the narrative differs when clustering algorithms form clubs for each region. This implies that at regional levels, achieving convergence clubs in renewable energy consumption for environmental sustainability is possible, most especially when realistic policies around macroeconomic, socio-economic and institutional quality variables are taken into account.

Exploration of the fipronil in egg contamination incident in the Netherlands using the Functional Resonance Analysis Method

Following the 2017 fipronil egg contamination incident in the European Union, improvements in safety management continue to be necessary, particularly for regulatory, preventive, and control activities. Drawing from the Dutch and European legislation, and the use of the Functional Resonance Analysis Method (FRAM), the aim of the study was to explore the regulatory framing of the elimination of red mites on poultry farms, the compliance of actual events in 2017 with these hygiene standards and regulations in order to reconcile actual practices with policy directives. The study considers the difference between policy implementation for work-as-imagined and the tasks undertaken in practice i.e., ‘work-as-done’. This allows for assessment and analysis of the gap between pre-defined hygiene policy and actual practice and allows for a systemic approach rather than a causal approach to examine the public health incident. The study concludes that it is important for high level policy makers to comprehend the challenges and barriers faced by those implementing policy, and how this could potentially mean that policy in practice is not aligned with what was originally intended. The presented analysis outlines the potential of the FRAM in assessing complex food systems to support a public health investigation of incidents, and to design practical and realistic food safety policies leading to higher levels of stakeholder compliance and improved safety management. • 2017 Fipronil in egg contamination incident in the Netherlands was explored. • Red mites were eliminated through practices that did not comply with regulations. • Performance variability in public hygiene policies was a key failure in work as done. • The use of FRAM was of value in assessing complex food systems.

Spatio-temporal assessing of natural vegetation regulation on SO2 absorption coupling ecosystem process model and OMI satellite data

Quantifying the contribution of natural ecosystems on air quality regulation can help to lay the foundation for ecological construction, and to promote the sustainable development of natural ecosystems. To identify the spatio-temporal dynamic changes of natural vegetation regulation on SO2 absorption and the underlying mechanism of these changes in Qinghai Province, an important ecological barrier and the unique natural ecosystems, the Biome-BGC model was improved to simulate the canopy conductance to SO2 and leaf area index (LAI) on the daily scale, and then the SO2 absorption by vegetation was estimated coupling SO2 concentration from satellite data. Our results showed that the annual average SO2 absorption of the natural ecosystems in Qinghai Province was 4.74 × 104 tons yr−1 from 2005 to 2018, accounting for about 40% of the total emissions. Spatially, the ecosystem service of SO2 absorption gradually decreased from southeast to northwest, and varied from 0 in Haixi state to 14.37 kg SO2 ha−1 yr−1 in Haibei state. The annual average SO2 absorption in unit area was 0.68 kg SO2 ha−1 yr−1, and significantly higher SO2 absorption was observed in summer with 0.45 kg SO2 ha−1 quarterly. The canopy conductance and LAI controlled by climate variables would be the dominant driving factors for the variation of SO2 absorption for natural ecosystems. The sensitivity analysis showed that SO2 concentration contributed more to the uncertainties of SO2 absorption than the conductance in this study. Our results could provide powerful supports for realistic eco-environmental policy and decision making.

Emerging Adults’ Awareness and Perceptions of Mental Health Problems and Services in Nigeria

Despite the high prevalence of psychiatric disorders among Nigerian youths, mental health care access and usage in this population is extremely low. This review examines emerging adults’ awareness and perceptions of mental health problems and services in Nigeria. Specifically, we (1) provide background information about mental health perception, services, and challenges in Nigeria; (2) describe the current state of mental health among the emerging adult population in Nigeria; (3) discuss risk factors among emerging adults in Nigeria; (4) document emerging adults’ perception of mental health problems and services in Nigeria, and potential explanations for this mental health trend. We conclude with a discussion of practices and policies. In a nation like Nigeria, where mental health services are scarce and health gaps and disparities abound, the value of mental health awareness and realistic health policies cannot be overstated.

Governance Transparency of Tax Revenue Performance in West Africa

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of governance and taxation revenue performance. The main purpose of the research is to examine the influence of management on tax revenue performance in West African countries. Specifically, the study aimed to investigate the impact of regulatory quality (political stability) and (voice and accountability) on tax revenue performance in West African countries; and to assess the effect of governance efficiency (the rule of law and control of corruption) on the performance of tax generation of West African countries. Secondary data were sourced from Governance indicators which cover 2005 to 2017. Regression analysis was employed to test the research hypotheses: regulatory quality does not significantly influence tax revenue performance in West African countries; and government efficiency does significantly affect tax revenue in West African countries. Sixteen West African countries were purposively chosen because of governance issues such as political instability and government ineffectiveness. The paper presents the results of an empirical analysis, which showed that regulatory quality, political stability and absence of violence, and voice and accountability have insignificant impacts (p-value>5% level of significance) on tax revenue performance. Moreover, government effectiveness, the rule of law and control of corruption have positive and significant impacts (p-value<5% level of significance) on tax revenue performance in West African countries. The study concludes that governance affects tax revenue performance in West African Countries; thus, the study recommends, among others that government should come up with realistic policies that will increase public and civil service quality.

US Researchers' Discourse and Reinterpretation of International Relation Theory on the 5‧18 Democratization Movement

This essay reinterprets the United States Government s role and responsibility of 5·18 democratization movement on the basis of academic products and presents new topics and research methods. For this, I study and analyze the preceding materials such as books and articles about the relationship between 5·18 and the United States. And then, I analyze the attitude of the US Government toward the New Korean Military Force of 1980s from the angel of international relations. Through the analysis of the reference, the Government and Americans have different ideas about the condition there. This research of the relationship between the the Korean and US Government up to the date around the sensational events like 5·18 democratization movement is expected to illuminate the American pragmatic and realist policy rather than the democratic justice, which might be understandable on the condition of reciprocal interaction.

Small-scale fisheries development in Africa: Lessons learned and best practices for enhancing food security and livelihoods

Small-scale fisheries (SSFs) play a significant role in ensuring food security, providing employment and generating livelihoods, however the sustainability and viability of their existence into the future is under threat with global pressures such as climate change, the increasing industrialisation of larger fishing activities and depleting fish stocks. The objectives of this article are to highlight the contributions of SSFs to poverty alleviation and food security and document the lessons learned and best practices for small-scale fisheries development in Africa to guide realistic policy reform and sustainable development projects. This paper brings together lessons from the development of Africa’s SSFs over the last thirty years alongside a range of case studies, taken from across the continent, of best practices for further development of SSFs from the perspective of food and nutrition security and of improving livelihoods and income. The key findings of best practices and their application to the sustainable development of African SSFs were: (i) supporting local or community governance; (ii) developing integrated, system-oriented policies which focus on the role SSFs play in food and nutrition security; (iii) investing in low cost innovation; (iv) diversifying fishing practices and livelihoods opportunities; and (v) supporting and cross-pollinating existing infrastructure and initiatives. The effective implementation of these practices by projects or governments necessitates the mobilisation of resources, on-the-ground engagement with stakeholders and using local knowledge to make meaningful change.

Scaling up nature-based solutions for climate-change adaptation: Potential and benefits in three European cities

Many exemplary projects have demonstrated that Nature-based Solutions (NBS) can contribute to climate change adaptation, but now the challenge is to scale up their use. Setting realistic policy goals requires knowing the amount of different NBS types that can fit in the urban space and the benefits that can be expected. This research aims to assess the potential for a full-scale implementation of NBS for climate-change adaptation in European cities, the expected benefits and co-benefits, and how these quantities relate to the urban structure of the cities.We selected three case studies: Barcelona (Spain), Malmö (Sweden), and Utrecht (the Netherlands), and developed six scenarios that simulate the current condition, the full-scale implementation of different NBS strategies (i.e., installing green roofs, de-sealing parking areas, enhancing vegetation in urban parks, and planting street trees), and a combination of them. Then we applied spatially-explicit methods to assess, for each scenario, two climate change-related benefits, i.e. heat mitigation and stormwater regulation, and three co-benefits, namely carbon storage, biodiversity potential, and overall greenness. Finally, by breaking down the results per land use class, we investigated how the potential and benefits vary depending on the urban form.Most scenarios provide multiple benefits, but each one is characterized by a specific mix. In all cities, a full-scale deployment of green roofs shows the greatest potential to reduce runoff and increase biodiversity, while tree planting -either along streets or in urban parks– produces the greatest impact on heat mitigation and greenness. However, these results entail interventions of different size and in different locations. Planting street trees maximizes interventions in residential areas, but key opportunities for integrating most NBS types also lie in commercial and industrial areas. The results on the pros and cons of each scenario can support policy-makers in designing targeted NBS strategies for climate change adaptation.

Enhancing policy realism in energy system optimization models: Politically feasible decarbonization pathways for the United States

In this paper, we adopt a novel approach to integrate political-organizational and techno-economic considerations to analyze decarbonization pathways for the United States. To do so, we first construct three portfolios of granular policies that target greenhouse gas (GHG) emissions reductions in the electricity, transportation, and buildings sectors, which we deem politically feasible under different federal political contexts. We then implement sectoral policy portfolios in the US-TIMES model and compare them to a business-as-usual (BAU) scenario and an 80% system-wide decarbonization scenario that uses stylized emissions constraints to produce the least-cost decarbonization pathway. Our findings reveal that greater political alignment enables electrification to play a more significant role as a central component of decarbonization. Renewable electricity generation and light-duty vehicle electrification both expand. Moreover, if the political environment allows more ambitious climate policies, deeper decarbonization can actually be achieved at a lower average abatement cost because more economically efficient policy instruments become politically feasible. However, our results indicate that none of our sectoral policy portfolios is sufficient to reduce system-wide GHG emissions by 80% by 2050. Major emissions sources for which new technologies and policies will be needed include heavy-duty vehicles, aviation, industrial production, and natural gas use in buildings.

Погляди Івана Вернадського на роль зовнішньоторговельної політики в економічному розвитку

Nowadays, the process of making effective economic decisions requires reference to the history of Ukrainian economic thought. The study of intellectual heritage and innovative ideas of prominent Ukrainian economists, among whom Ivan Vernadsky occupies an important place, will enrich the understanding of the mechanisms and ways of modern economic transformation. The purpose of the article is to analyze and generalize Ivan Vernadsky’s conceptual views on the role of foreign trade policy in economic development. The theoretical basis of this study is conceptual approaches to understanding the nature of foreign trade policy, in particular, protectionism and free trade. Systematic, comparative-historical, institutional-evolutionary, and historical-genetic analyses were used as the research methodology. The author considers Ivan Vernadsky’s conceptual approach to foreign trade as a basis for providing the country's economic leadership in the international area. The economist’s ideas on the advantages of liberal foreign trade policy, free trade, and its mutual benefits for countries are revealed. Ivan Vernadsky was a staunch opponent of restrictive foreign trade policy, which creates obstacles to the country's competitive advantages and economic progress. Attention was paid to Ivan Vernadsky's criticism of customs protectionism. According to the scientist's point of view, protectionism leads to monopolization, price rises, technical and technological backwardness of production, destabilization of foreign trade relations, etc. At the same time, one of the scientist’s merits is the formation of an innovative approach to the interpretation of protectionism as a general economic doctrine and a realistic economic policy. Ivan Vernadsky’s vision of the basics of efficient management is generalized. He creates an original theory of economic development, which can be used for selection of effective mechanisms of modern economic policy.

Can local policy options reverse the decline process of small and marginalized rural areas influenced by global change?

Rural depopulation generates deep territorial imbalances, threats regional food security, and causes the irreversible loss of culture and local institutions that manage natural resources and ecosystem services worldwide. While local leadership and economic diversification have been pointed as factors that could trigger rural development, what happens to remote rural areas whose continuous process of depopulation has undermined their social capital and leadership and their endogenous capacity for economic diversification? What realistic policy options could trigger an effective and endogenous rural development process in these weakened areas? Here we used a dynamic simulation model and a sensitivity analysis to explore the long-term effects of local policy options suggested by institutional, academic and local stakeholders that could act on leverage points to revert the depopulation of a marginalized rural area in Mexico, the oasis of Comondú in Baja California Sur. The identified leverage points are related to improving the production yields of irrigated agriculture and livestock farming, the main economic activities of this social-ecological system. Our results showed the positive, but limited, effects of acting on these leverage points. However, they seem plausible good places to act to start an endogenous revitalization process in this rural area. We found complementariness between the stakeholders’ management proposals, and high proximity of these proposals to the leverage points, especially the most place-based-specific proposals. This study shows the relevance of place-based research for rural development and how modeling is a valuable decision support tool to evaluate in advance the effectiveness of policy options proposed by stakeholders.

Construction of the Policy Network Analysis Framework for the Implementation of China’s Higher Education Informatization Policy

The research on higher education informatization policy is actually a theoretical abstraction of realistic policy implementation, and it is also a research direction that is fully applicable to China’s local application and theoretical interpretation. Due to the special nature of education policy, it is not advisable to explain policy results purely based on actors or structural characteristics of the policy network. It should be more in line with the social reality of multi-party’s full participation in benefit games, multiple social organizations, and the social difference pattern of China, and step from the causality between a specific policy network and a specific policy result towards a concrete policy network interpretation framework.

Divergent views on trophy hunting in Africa, and what this may mean for research and policy

AbstractOver the past decade, trophy hunting in Africa has seen increased public and scientific interest. Much of that attention has come from outside of Africa, with little emphasis on local views. We circulated an online survey through international networks to explore demographic and regional differences in opinion regards support for African trophy hunting, trophy import bans, and outside funding of conservation estates supported by hunting. We received ∼5700 responses and found that location, demography, and conservation background influenced opinion. African and North American respondents showed (significantly) more support for trophy hunting than respondents from Europe or other areas, as did respondents with conservation backgrounds. Unlike North Americans, Africans supported external subsidies of wildlife areas presently funded by hunting. Many factors affected opinions on African hunting, but respondent location played a major role. Realistic policy on African trophy hunting should thus integrate African perspectives, in particular those of rural communities.

A mathematical view towards improving undergraduate student performance and mitigating dropout risks

In this paper, we assess the relevance of social and cognitive factors such as self-efficacy, locus of control and exposure to negative social influence in relation to undergraduate student dropout. To this purpose, we analyze a compartmental model involving a system of nonlinear ODEs, which is loosely based upon the SIR model of mathematical epidemiology and describes the academic performance of the student population. We examine threshold values that govern the stability of the equilibria and can be viewed as target values to be reached in order to alleviate undergraduate students dropout. A backward bifurcation is observed to occur, analytically and numerically, provided that certain conditions are satisfied.
 A sensitivity analysis is then performed to find how the threshold values respond to changes in the parameters, a procedure for estimating these parameters being also proposed. Concrete values are then computed using survey data from a Ghanaian university. The impact of parameter variation upon the dynamics of the system, particularly on certain population sizes and on threshold values, is also numerically illustrated. Our findings are then interpreted from a social cognitive perspective, realistic policy changes being proposed along with appropriate teaching and coaching strategies.

Base Station Power Optimization for Green Networks Using Reinforcement Learning

The next generation mobile networks have to provide high data rates, extremely low latency, and support high connection density. To meet these requirements, the number of base stations will have to increase and this increase will lead to an energy consumption issue. Therefore “green” approaches to the network operation will gain importance. Reducing the energy consumption of base stations is essential for going green and also it helps service providers to reduce operational expenses. However, achieving energy savings without degrading the quality of service is a huge challenge. In order to address this issue, we propose a machine learning based intelligent solution that also incorporates a network simulator. We develop a reinforcement-based learning model by using deep deterministic policy gradient algorithm. Our model update frequently the policy of network switches in a way that, packet be forwarded to base stations with an optimized power level. The policies taken by the network controller are evaluated with a network simulator to ensure the energy consumption reduction and quality of service balance. The reinforcement learning model allows us to constantly learn and adapt to the changing situations in the dynamic network environment, hence having a more robust and realistic intelligent network management policy set. Our results demonstrate that energy efficiency can be enhanced by 32% and 67% in dense and sparse scenarios, respectively.

Experiential Learning as a Way to Foster Realistic Comparative Policy Analysis

This paper highlights the comparative value of an international capstone course on sustainable water management in a graduate public and international affairs program. By exposing students to experiential learning in two contexts, students develop an in-depth understanding of policy and can make realistic comparative policy analysis and reflect on the implementation challenges. I argue that students’ reflection is of understanding in practice the limitations and possibilities of transferability of policies and practices. By using the SDG #6 on water as a framework; students develop an in-depth understanding of policies that aim to address global challenges at the local level. My course adds on what others have argued are the benefits of reflection and action for students’ education, and more specifically on the students’ exposure to the comparative policy in context.

Base Station Power Optimization for Green Networks Using Reinforcement Learning

The next generation mobile networks have to provide high data rates, extremely low latency, and support high connection density. To meet these requirements, the number of base stations will have to increase and this increase will lead to an energy consumption issue. Therefore "green" approaches to the network operation will gain importance. Reducing the energy consumption of base stations is essential for going green and also it helps service providers to reduce operational expenses. However, achieving energy savings without degrading the quality of service is a huge challenge. In order to address this issue, we propose a machine learning based intelligent solution that also incorporates a network simulator. We develop a reinforcement based learning model by using deep deterministic policy gradient algorithm. Our model update frequently the policy of network switches in a way that, packet be forwarded to base stations with an optimized power level. The policies taken by the network controller are evaluated with a network simulator to ensure the energy consumption reduction and quality of service balance. The reinforcement learning model allows us to constantly learn and adapt to the changing situations in the dynamic network environment, hence having a more robust and realistic intelligent network management policy set. Our results demonstrate that energy efficiency can be enhanced by 32% and 67% in dense and sparse scenarios, respectively.

Background of Achieving a Realistic Legislative Criminal Policy in Iranian Penal Laws

For a criminal policy, in the broadest sense, to be successful and compatible with a realistic view of the criminal phenomenon in the field of pragmatism judgment and to achieve its objectives, it needs a background which, in its absence, not only laws based on realistic criminal policy fail, but their application in such a situation will cause a double damage to society: legal and moral. Apply methods of social prevention in the economic and cultural dimension, observing the principle of minimum criminal law, the mandatory anticipation of the presentation of a personality profile in all crimes committed and finally, the establishment of a care administration to comply with the implementation of realistic laws in the best possible way. It is concluded that this path that combines criminal policy and pragmatic legal realism is one of the desired areas in question in the field of criminal investigation in Iran. This research, which is conducted using the content analysis method, identifies the background for the implementation and enforcement of a realistic legislative criminal policy in Iran to remove obstacles to this advanced scientific knowledge.