China’s Climate Policy:Mandate-Based vs.Market-Based Approaches

Mandate-based and market-based mechanisms represent two primary approaches to achieving policy objectives,yet the debate over their relative effectiveness remains unresolved.The mandate-based approach is exemplified by pilot programs for low-carbon provinces and cities,referred to as“Low-Carbon Pilot Provinces/Cities”,while the market-based mechanism is reflected in pilot programs for carbon emissions trading markets,or“Carbon Trading Pilot Programs”.This paper employs event study analysis to compare the carbon emission reduction impacts of these two approaches.Our findings reveal that the Low-Carbon Pilot Provinces/Cities achieved emissions reduction primarily by curbing economic output,without significantly reducing carbon emissions intensity.In contrast,the Carbon Trading Pilot Programs led to an increase in total carbon emissions by driving economic growth,even as they reduced carbon emissions intensity.A heterogeneity analysis further indicates that the emissions reductions observed in the Low-Carbon Pilot Provinces/Cities were predominantly concentrated in economically less-developed regions,whereas the increase in carbon emissions associated with the Carbon Trading Pilot Programs was more significant in regions with lower initial carbon emissions intensity.Against the backdrop of China’s efforts to achieve its carbon peak and neutrality goals,this paper offers valuable insights for the design of effective climate policies.

Digital Economy and Corporate Innovation-Washing--An Empirical Study on How Information Mitigates Policy Distortion

As stated in the Report to the 20th National Congress of the Communist Party of China(CPC),innovation remains at the heart of China’s modernization drive,and it is vital to optimize the allocation of innovation resources,deepen structural scientific and technological reforms,and enhance the overall performance of China’s innovation system.Government incentives have boosted firm R&D and innovation efforts;however,they have also triggered an innovation dilemma where enterprises,capitalizing on their informational advantages,resort to innovation-washing behaviors that undermine the intended purpose of the policies.Based on the information asymmetry theory,this paper conducts an empirical study on how the digital economy affects firms’innovation-washing behavior.The development of the regional digital economy could suppress firm innovation-washing behavior in the region,and such a mitigation effect is primarily caused by an increase in the number of digital industry professionals.According to our heterogeneity analysis,the digital economy has a greater impact on firm innovation-washing behavior for certain types of enterprises,including non-state-owned enterprises(non-SOEs),small and medium-sized enterprises(SMEs),enterprises in less competitive industries,and enterprises in unfavorable business environments.Our mechanism analysis revealed that the digital economy may restrain innovation-washing behavior by reducing information asymmetry between enterprises and external stakeholders.In terms of economic outcomes,the digital economy has the potential to directly influence firm innovation output while also indirectly mitigating the subsequent decline in innovation output by discouraging innovation-washing.This paper enriches the research findings on how the digital economy breaks down“information silos”and offers a potential solution to the“emphasis on input and quantity over quality and efficiency”phenomenon in science and technology innovation practices.

Deep reinforcement learning based integrated evasion and impact hierarchical intelligent policy of exo-atmospheric vehicles

Exo-atmospheric vehicles are constrained by limited maneuverability,which leads to the contradiction between evasive maneuver and precision strike.To address the problem of Integrated Evasion and Impact(IEI)decision under multi-constraint conditions,a hierarchical intelligent decision-making method based on Deep Reinforcement Learning(DRL)was proposed.First,an intelligent decision-making framework of“DRL evasion decision”+“impact prediction guidance decision”was established:it takes the impact point deviation correction ability as the constraint and the maximum miss distance as the objective,and effectively solves the problem of poor decisionmaking effect caused by the large IEI decision space.Second,to solve the sparse reward problem faced by evasion decision-making,a hierarchical decision-making method consisting of maneuver timing decision and maneuver duration decision was proposed,and the corresponding Markov Decision Process(MDP)was designed.A detailed simulation experiment was designed to analyze the advantages and computational complexity of the proposed method.Simulation results show that the proposed model has good performance and low computational resource requirement.The minimum miss distance is 21.3 m under the condition of guaranteeing the impact point accuracy,and the single decision-making time is 4.086 ms on an STM32F407 single-chip microcomputer,which has engineering application value.

Timely Policy Exit:Reducing Over-Investment and Driving High-Quality Firm Performance

Using data from the 11th to 14th Five-Year Plan periods(2006-2025),this study applies a Difference-in-Differences(DID)approach to assess the impact of industrial policy withdrawal.Industries that have faced policy withdrawal for over a decade are categorized as the treatment group,while consistently supported industries form the control group.The analysis examines how withdrawal affects firm total factor productivity(TFP)and investment behavior.The results show that policy withdrawal boosts firm TFP by reducing over-investment and improving the efficiency of R&D spending.This effect is particularly evident in industries with strong,competitive leading firms.Additionally,in regions with lower levels of marketization,timely policy withdrawal plays a key role in curbing over-investment.This study also highlights a dual effect of policy withdrawal:while it fosters corporate social responsibility,it may also encourage financial speculation.These findings suggest that the implementation of industrial policy should provide“timely assistance”over a limited timeframe rather than long-term support to well-established industries.As industries mature,policy support should be gradually reduced or phased out to avoid over-investment and enhance firm efficiency.

A quantitative study of disruptive technology policy texts:An example of China’s artificial intelligence policy

Purpose:The transformative impact of disruptive technologies on the restructuring of the times has attracted widespread global attention.This study aims to analyze the characteristics and shortcomings of China’s artificial intelligence(AI)disruptive technology policy,and to put forward suggestions for optimizing China’s AI disruptive technology policy.Design/methodology/approach:Develop a three-dimensional analytical framework for“policy tools-policy actors-policy themes”and apply policy tools,social network analysis,and LDA topic model to conduct a comprehensive analysis of the utilization of policy tools,cooperative relationships among policy actors,and the trends in policy theme settings within China’s innovative AI technology policy.Findings:We find that the collaborative relationship among the policy actors of AI disruptive technology in China is insufficiently close.Marginal subjects exhibit low participation in the cooperation network and overly rely on central subjects,forming a“center-periphery”network structure.Policy tool usage is predominantly focused on supply and environmental types,with a severe inadequacy in demand-side policy tool utilization.Policy themes are diverse,encompassing topics such as“Intelligent Services”“Talent Cultivation”“Information Security”and“Technological Innovation”,which will remain focal points.Under the themes of“Intelligent Services”and“Intelligent Governance”,policy tool usage is relatively balanced,with close collaboration among policy entities.However,the theme of“AI Theoretical System”lacks a comprehensive understanding of tool usage and necessitates enhanced cooperation with other policy entities.Research limitations:The data sources and experimental scope are subject to certain limitations,potentially introducing biases and imperfections into the research results,necessitating further validation and refinement.Practical implications:The study introduces a three-dimensional analysis framework for disruptive technology policy texts,which is significant for formulating and enhancing disruptive technology policies.Originality/value:This study utilizes text mining and content analysis techniques to quantitatively analyze disruptive technology policy texts.It systematically evaluates China’s AI policies quantitatively,focusing on policy tools,policy actors,policy themes.The study uncovers the characteristics and deficiencies of current AI policies,offering recommendations for formulating and enhancing disruptive technology policies.

SRv6 Policy业务可靠性方案探讨

介绍了SRv6 Policy、SBFD技术及5G承载网络SRv6 Policy业务可靠性方案。针对SBFD误触发问题,提出了在被动端生成BSID、部署引流策略及设置不同检测周期等3种完善措施,这些措施不仅提高了业务的可靠性,还显著提升了网络服务能力.

A Study on the Multiple Differential Structure of Development in China^s Ethnic Areasand Exploiting the Differentiation and Collaborative Policy—On the New Form of China’s Ethnic Relations and the New System of Ethnic Policies

A fter 60 years of im plem entation, the ethnic regional autonomous policy has provided basic p o litica l support for promoting the common development and prosperity of a ll ethnic groups.

A View of Beijing’s Traffic Policy:Evaluation on the Policies Released in 2010 to Ease Traffic Congestion

In today’s society where the economy is developing rapidly and the process of urbanization is accelerating,the traffic in major cities in China is facing tremendous pressure.The economy of Beijing has developed rapidly,its population is dense,the living standard of people has improved significantly,and the number of cars has increased dramatically.From the end of 2005 to the end of November 2010,motor vehicles in Beijing increased from about 2.58 million to about 4.69 million.The problem of traffic congestion has become more prominent,affecting the daily lives of the residents.

Policy Framework for Community and State Policing in Combating Rising Security Challenges in Nigeria

Viability of decentralizing policing in Nigeria had been on the front burner of security discourse since Nigeria returned to democratic governance in 1999.Valid points had been put forward by both those in support and those in opposition.The Community Policing Department of the Nigeria Police had remained more of an administrative unit with little impact beyond the Police Community Relations Committee activities.Rising cases of herdsmen attacks of various communities,terrorist insurgency in the North-East,kidnappings across the different geo-political zones had resulted in the need to interrogate the efficacy of effective community policing and state policing as viable options to combating rising security challenges.The study adopted qualitative method,and being a library research relied entirely on secondary data.Sources of data included journals,relevant textbooks,newspapers,magazines,and materials downloaded from internet.The paper argues that the traditional security agencies had failed to effectively combat the many security challenges that Nigeria faces.The combination of the official security agencies and the military had failed to effectively combat insecurity in the country.The local vigilante groups on the other hand had made valuable inroad in curtailing some of the security challenges including terrorist insurgency as a result of their knowledge of the terrain.The paper concludes that to effectively combat the many security challenges,there is a need for new policy framework at the federal and state levels that would decentralize policing and give legal backing for collaboration between the official security agencies under the federal government and state security outfits including the vigilante.

Policy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal Control

Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is used to evaluate the policy.In the policy improvement process,the policy gradient based method is employed.

Health financing policies in Sub-Saharan Africa:government ownership or donors’influence?A scoping review of policymaking processes

Background:The rise on the international scene of advocacy for universal health coverage(UHC)was accompanied by the promotion of a variety of health financing policies.Major donors presented health insurance,user fee exemption,and results-based financing policies as relevant instruments for achieving UHC in Sub-Saharan Africa.The“donor-driven”push for policies aiming at UHC raises concerns about governments’effective buy-in of such policies.Because the latter has implications on the success of such policies,we searched for evidence of government ownership of the policymaking process.Methods:We conducted a scoping review of the English and French literature from January 2001 to December 2015 on government ownership of decision-making on policies aiming at UHC in Sub-Saharan Africa.Thirty-five(35)results were retrieved.We extracted,synthesized and analyzed data in order to provide insights on ownership at five stages of the policymaking process:emergence,formulation,funding,implementation,and evaluation.Results:The majority of articles(24/35)showed mixed results(i.e.ownership was identified at one or more levels of policymaking process but not all)in terms of government ownership.Authors of only five papers provided evidence of ownership at all reviewed policymaking stages.When results demonstrated some lack of government ownership at any of the five stages,we noticed that donors did not necessarily play a role:other actors’involvement was contributing to undermining government-owned decision-making,such as the private sector.We also found evidence that both government ownership and donors’influence can successfully coexist.Discussion:Future research should look beyond indicators of government ownership,by analyzing historical factors behind the imbalance of power between the different actors during policy negotiations.There is a need to investigate how some national actors become policy champions and thereby influence policy formulation.In order to effectively achieve government ownership of financing policies aiming at UHC,we recommend strengthening the State’s coordination and domestic funding mobilization roles,together with securing a higher involvement of governmental(both political and technical)actors by donors.

Research on Policy Diffusion Path and Reproduction of River Chief System

The River Chief System (RCS) has evolved from local innovative practices to a national water governance strategy to address the current challenges in China’s water environmental management. In contrast to existing research that focuses on the strengths, weaknesses, and improvements of RCS, this study uses literature study to reveal the dynamic evolution of RCS through three phases, with RCS spreading from developed coastal areas to central and western inland regions. RCS’s diffusion path involves vertical diffusion between central and local levels and horizontal diffusion among local governments. Moreover, RCS has also achieved conceptual spillover, gradually expanding into other governance domains, such as the Lake Chief System, the Field Chief System, the Forestry Chief System, and the integration of multiple chief roles. However, it is essential to scrutinize the phenomenon of applying similar governance mechanisms to different areas, as it may result in challenges such as overburdening local governments, insufficient public participation, oversimplification of differences in natural resource endowments, and limited applicability. This study also provides suggestions on how to address these challenges. The study contributes theoretical insights and policy implications, providing a foundation for practical policy innovation.

Inactivated H9N2 vaccines developed with early strains do not protect against recent H9N2 viruses:Call for a change in H9N2 control policy

H9N2 virus has been widely distributed in wild birds and poultry around the world since its first emergence in the United States of America in 1966(Gu et al.2017;Carnaccini and Perez 2020).The virus appeared in chickens in China in the early 1990s,and over the last two decades has gradually become the dominant epidemic subtype(Sun and Liu 2015;Bi et al.2020).Although H9N2 virus infection alone cannot cause severe disease or death in poultry,H9N2 virus-infected birds experience a degree of egg production drop and can be easily infected by other pathogens,thus causing economic losses for poultry industry.

Automatic Generation of Attribute-Based Access Control Policies from Natural Language Documents

In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.

Big Data Analysis of Policy Coordination Paths Based on Latent Dirichlet Allocation Model and Fuzzy-Set Qualitative Comparative Analysis Method

The selection and coordinated application of government innovation policies are crucial for guiding the direction of enterprise innovation and unleashing their innovation potential.However,due to the lengthy,voluminous,complex,and unstructured nature of regional innovation policy texts,traditional policy classification methods often overlook the reality that these texts cover multiple policy topics,leading to lack of objectivity.In contrast,topic mining technology can handle large-scale textual data,overcoming challenges such as the abundance of policy content and difficulty in classification.Although topic models can partition numerous policy texts into topics,they cannot analyze the interplay among policy topics and the impact of policy topic coordination on enterprise innovation in detail.Therefore,we propose a big data analysis scheme for policy coordination paths based on the latent Dirichlet allocation(LDA)model and the fuzzyset qualitative comparative analysis(fsQCA)method by combining topic models with qualitative comparative analysis.The LDA model was employed to derive the topic distribution of each document and the word distribution of each topic and enable automatic classi-fication through algorithms,providing reliable and objective textual classification results.Subsequently,the fsQCA method was used to analyze the coordination paths and dynamic characteristics.Finally,experimental analysis was conducted using innovation policy text data from 31 provincial-level administrative regions in China from 2012 to 2021 as research samples.The results suggest that the proposed method effectively partitions innovation policy topics and analyzes the policy configuration,driving enterprise innovation in different regions.

Scope of public health workforce: an exploratory analysis on World Health Organization policy and the literature

The public health workforce is a key component of public health system.To articulate the scope of public health workforce,we reviewed the relevant World Health Organization(wHO)guidance and peer-reviewed journal articles on this subject.Specifically,we assessed and compared the relevant publications produced by WHO Headquarters and Regional Offices along with other literature on this issue.Our focus was on the“occupation,workplace setting,and employer of public health workforce”.It is noteworthy that WHO has adopted a conceptual framework with an inclusive scope of the public health workforce,while setting out a 5-year vision to strengthen capacity across all WHO Member States for a multidisciplinary workforce to deliver the essential public health functions,including emergency preparedness and response.The importance of public health workforce in global and national responses to the coronavirus disease 2019(COVID-19)pandemic is recognized.We also observed that there were diverse understandings of the scope of public health workforce worldwide,including macro-,meso-and micro-level perspectives.In the post-COVID-19 era,we suggest that policy-makers and practitioners at the national,regional and global level adopt a coordinated approach to expand and strengthen the national workforce as guided by the WHO towards the health-related targets of United Nations Sustainable Development Goals such as health security and Universal Health Coverage.

Mapping Climate Services for Disaster Risk Management: A Systematic Review and Research Gaps from a Policy Process Perspective

Climate services (CS) are crucial for mitigating and managing the impacts and risks associated with climate-induced disasters. While evidence over the past decade underscores their effectiveness across various domains, particularly agriculture, to maximize their potential, it is crucial to identify emerging priority areas and existing research gaps for future research agendas. As a contribution to this effort, this paper employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the state-of-the-art in the field of climate services for disaster risk management. A comprehensive search across five literature databases combined with a snowball search method using ResearchRabbit was conducted and yielded 242 peer-reviewed articles, book sections, and reports over 2013-2023 after the screening process. The analysis revealed flood, drought, and food insecurity as major climate-related disasters addressed in the reviewed literature. Major climate services addressed included early warning systems, (sub)seasonal forecasts and impact-based warnings. Grounded in the policy processes’ theoretical perspective, the main focus identified and discussed three prevailing policy-oriented priority areas: 1) development of climate services, 2) use-adoption-uptake, and 3) evaluation of climate services. In response to the limitations of the prevalent supply-driven and top-down approach to climate services promotion, co-production emerges as a cross-cutting critical aspect of the identified priority areas. Despite the extensive research in the field, more attention is needed, particularly pronounced in the science-policy interface perspective, which in practice bridges scientific knowledge and policy decisions for effective policy processes. This perspective offers a valuable analytical lens as an entry point for further investigation. Hence, future research agendas would generate insightful evidence by scrutinizing this critical aspect given its importance to institutions and climate services capacity, to better understand intricate facets of the development and the integration of climate services into disaster risk management.

Geographical Distribution of Atmospheric Nitrogen Deposition in China and Its Response to Emission Control Policy

Atmospheric nitrogen(N)deposition has experienced significant change because of anthropogenic emissions,thereby exerting a pronounced impact on global ecosystem services.With the rapid development of industry and agriculture and the swift expansion of urban areas in China since the 1980s,reactive nitrogen(Nr)emissions and N deposition have substantially increased.In pursuit of im-proving air quality,China has implemented a series of environmental protection policies and undertaken diverse measures to reduce pol-lutant emissions.This paper is a review of multivariate data sources of atmospheric N deposition based on the results of literature from 1980 to 2023,and the original data from 1980 to 2020 are summarized,counted and calculated.The main findings are as follows:1)the annual average atmospheric N deposition ranged from approximately 20-40 kg/(ha·yr),with the variability primarily linked to different assessment methods;2)regional disparities were evident in the spatial distribution of N deposition,with elevated values concentrated in areas with intense Nr emissions;3)atmospheric N deposition significantly declined after 2010,particularly the deposition of oxidized N,while reduced N deposition remained stable.These results reflect the effects of China's serious control policies on nitrogen oxide(NO.)emissions and strengthen the importance of agricultural NH3 emission mitigation.This study contributes to a comprehensive understanding of the N dynamics in the emission-deposition process,and provides a scientific foundation for the research of environmental protection,climate change,and sustainable development.

The Adjustment of NATO’s Space Policy and Its Implications

Under the US leadership,NATO has been adjusting its space policy and strengthening its space deterrence capabilities to address the so-called“threat”from China and Russia.While the deterrent effect of NATO’s space policy remains to be seen,the various measures taken to implement the policy will have a considerable impact on the global space landscape,accelerating the weaponization of space and making it more difficult to prevent an arms race in space and govern space security.

POLICIES

China to Maintain Supportive Monetary Policy in 2025 China’s central bank will maintain a supportive monetary policy stance and policy orientation in 2025,its governor said.The People’s Bank of China(PBOC)will utilize a variety of monetary policy tools and increase countercyclical regulation to maintain reasonable and ample liquidity,and to reduce the overall financing costs for enterprises and residents,PBOC governor Pan Gongsheng said while addressing a conference.Efforts will be made to effectively leverage structural monetary policy tools to promote the stable development of the real estate market and capital market,Pan said.The PBOC announced that starting from January 2025,a new statistical caliber of M1 money supply will be implemented,which will include personal demand deposits and non-bank payment institutions’customer reserves.The central bank will enhance its monitoring of the money supply at various levels and social liquidity,Pan noted.