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Poverty alleviation has been a major theme of China's modernization process since the founding of New China. This paper points out that China's poverty alleviation process presents three stylized facts: “Miraculous” achievements of poverty alleviation have been made on a global scale; the poverty alleviation achievements mainly occurred in the high growth stage after reform and opening up; the poverty alleviation process is accompanied by the structural transformation of the urban–rural dual economy.

Therefore, a logically consistent analytical framework should form among the structural transformation of the dual economy, economic growth and the achievements in poverty alleviation. In logical deduction, the structural transformation of the dual economy affects rural poverty alleviation through the effects of labor reallocation, agricultural productivity improvement, demographic change and fiscal resource allocation.

The first two refer to economic growth, and the latter two are alleviation policies. The combination of economic growth and poverty alleviation policies is the main cause for poverty alleviation performance. China's empirical evidence can support the four effects by which the structural transformation of the dual economy affects poverty alleviation.

China's socialist system and its economic system transformation after reform and opening up provide an institutional basis for the effects to come into play. After 2020, China's poverty alleviation strategies will enter the “second-half” phase, namely, the phase of solving the problems of relative poverty in urban and rural areas by adopting conventional methods and establishing long-term mechanisms. This requires the facilitation of the reconnection between poverty alleviation strategies and the structural transformation of the dual economy in terms of development ideas and policy directions.

The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of the inherent characteristics of the disabled populations, so that working plans and policies, which can effectively help the disabled populations, can be made accordingly.

In this paper, the authors proposed a big data management and analytic approach for disability datasets.

By using a set of data mining algorithms, the proposed approach can provide the following services. The data management scheme in the approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. The data mining scheme in the approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments based on real-world dataset are conducted at the end to prove the effectiveness of the approach.

The proposed approach can enable data-driven decision-making for professionals who work with disabled populations.

Background: Rising food bank usage in the UK suggests a growing prevalence of food insecurity. However, a formalised, representative measure of food insecurity was not collected in the UK until 2019, over a decade after the initial proliferation of food bank demand. In the absence of a direct measure of food insecurity, this article identifies and summarises longitudinal proxy indicators of UK food insecurity to gain insight into the growth of insecure access to food in the 21st century.

Methods: A rapid evidence synthesis of academic and grey literature (2005–present) identified candidate proxy longitudinal markers of food insecurity. These were assessed to gain insight into the prevalence of, or conditions associated with, food insecurity.

Results: Food bank data clearly demonstrates increased food insecurity. However, this data reflects an unrepresentative, fractional proportion of the food insecure population without accounting for mild/moderate insecurity, or those in need not accessing provision. Economic indicators demonstrate that a period of poor overall UK growth since 2005 has disproportionately impacted the poorest households, likely increasing vulnerability and incidence of food insecurity. This vulnerability has been exacerbated by welfare reform for some households. The COVID-19 pandemic has dramatically intensified vulnerabilities and food insecurity. Diet-related health outcomes suggest a reduction in diet quantity/quality. The causes of diet-related disease are complex and diverse; however, evidence of socio-economic inequalities in their incidence suggests poverty, and by extension, food insecurity, as key determinants.

Conclusion: Proxy measures of food insecurity suggest a significant increase since 2005, particularly for severe food insecurity. Proxy measures are inadequate to robustly assess the prevalence of food insecurity in the UK. Failure to collect standardised, representative data at the point at which food bank usage increased significantly impairs attempts to determine the full prevalence of food insecurity, understand the causes, and identify those most at risk.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

Background: Evidence suggests that people living in poverty often experience inadequate nutrition with short and long-term health consequences. Whilst the diets of low-income households have been subject to scrutiny, there is limited evidence in the UK on the diet quality and food practices of households reporting food insecurity and food bank use. We explore lived experiences of food insecurity and underlying drivers of diet quality among low-income families, drawing upon two years of participatory research with families of primary school age children.

Methods: We report on a mixed-methods study of the relationship between low income, food bank use, food practices and consumption from a survey of 612 participants, including 136 free text responses and four focus groups with 22 participants. The research followed a parallel mixed-methods design: qualitative and quantitative data were collected separately, although both were informed by participatory work. Quantitative data were analysed using binary and multinomial logistic regression modelling; qualitative data were analysed thematically.

Results: Lower income households and those living with food insecurity struggle to afford a level of fruit and vegetable consumption that approaches public health guidance for maintaining a healthy diet, despite high awareness of the constituents of a healthy diet. Participants used multiple strategies to ensure as much fruit, vegetable and protein consumption as possible within financial constraints. The quantitative data suggested a relationship between higher processed food consumption and having used a food bank, independent of income and food security status.

Conclusions: The findings suggest that individualised, behavioural accounts of food practices on a low-income misrepresent the reality for people living with poverty. Behavioural or educational interventions are therefore likely to be less effective in tackling food insecurity and poor nutrition among people on a low income; policies focusing on structural drivers, including poverty and geographical access to food, are needed.

Aiding employment is an important poverty reduction strategy in many countries’ social welfare systems, as this strategy can help empower the recipients with a better living standard, development and social inclusion. The purpose of this paper is to identify the most significant individual and systematic variables for the employment status of low-income groups in urban China.

The data of this study are drawn from “Social Policy Support System for Poverty-stricken Families in Urban and Rural China 2015” report. The Ministry of Civil Affairs of the People’s Republic of China appointed and funded the Institute of Social Science Survey (ISSS) at Peking University to deliver the related project and organize a research team to write the report. Multiple binary logistic regression analysis is adopted to identify both individual and systematic factors that affect the employment status among low-income groups in urban China.

According to the results of the binary logistic regression model, individual factors, including: gender; householder status; education; and self-rated health status, play a significant role in determining the employment status of low-income groups in urban China. Clearly, the impacts of individual factors are more influential to marginal families than to families entitled to receive Basic Living Allowance. In contrast, compared with marginal families, systematic factors are more influential to families entitled to receive Basic Living Allowance.

This study highlights the importance of precise poverty reduction strategy and the issue of “welfare dependence” among low-income groups in urban China. Policy recommendations derived from the findings are hence given, including: the promotion of family-friendly policies; the introduction of a smart healthcare system; the establishment of a Basic Living Allowance adjustment mechanism; and the provision of related social services.

In 2009, the Liberal government of Ontario released their first “streamlined” poverty reduction strategy to end child poverty in the province. The strategy was renewed in 2014, and an updated strategy was released in 2021 by the Conservative government of Ontario. Based on ongoing research, this chapter explores how these Poverty reduction strategies mobilize a historical conception of low-income urban environments as threats to child development. I show that, rather than end poverty, these conceptions are used to justify community revitalization efforts that displace low-income populations while prioritizing and benefiting private market investment. Central to these strategies is the figure of the child, who is constructed as innocent and vulnerable, requiring protection and saving from the perils of poverty by middle- and upper-class interventions. The chapter concludes by examining the neoliberal logic that continues to inform the 2021 strategy.

As the essential requirement of socialism with Chinese characteristics, common prosperity stands for both the goal of and the approach to economic growth. Shared development is a new stage of the process of common prosperity. From the perspective of economic growth, it requires the low- and middle-income groups to gain more from the growth than high-income groups. The paper aims to discuss these issues.

Based on provincial panel data, the random effect model and the dynamic panel model are used in this paper to analyze the path to achieve pro-poor growth.

The keys to achieve pro-poor growth are first to promote new urbanization with people at the center, diversify the forms of employment and improve the income structure of the residents, and second to improve the accuracy in designing redistribution policies.

After the realization of “some get rich first” policy, it is important to swiftly adapt to a new mindset of shared development, which charters a new course to the Marxist common prosperity. There exist few established economic theories or action plans with respect to shared development. Pro-poor growth, however, offers a perspective to achieve both sharing and development.

We implement an inductive, case study approach to explore the motivations and methods of five successful social entrepreneurs. Our findings show that founders noticed, felt, and responded to someone else's pain, demonstrating compassion as the genesis of the business venture. Successful social innovation, however, was the result of the creation of an organization structured to include diverse stakeholder input and participation in the decision-making process. Thus, compassion motivates entrepreneurs to pursue broad gains as opposed to singular interests and enhances a willingness to incorporate others' ideas through an open-strategy process. Our study suggests that interaction with stakeholders can impact the structure of the firm, the business model it employs, and intended and unintended business consequences.