Population Poverty Research Articles

Blessed are the peacemakers: The future burden of intrastate conflict on poverty

Intrastate conflict generally undermines human development but its effect on global poverty across different income thresholds remains poorly understood. This paper analyzes how many people will live in poverty due to intrastate civil conflict in 2030, 2050, and 2070 using the International Futures model and shared socioeconomic pathways, forecasting 12 scenarios for 179 countries. A baseline conflict scenario leads to an additional 148.2 million (range: 50.7 to 186.0 million) people living in extreme poverty (<$1.90 per day) due to conflict by 2030 compared with a scenario where conflict is eliminated starting in 2022. These conflict-attributable poor represent 20.1% of the population in extreme poverty at that time, with the majority living in South Asia followed by Africa. By 2050 the population living in conflict-attributable poverty increases to 164.9 million (range: 4.4 to 376.5 million), representing 32.7% of the total extremely poor population at that time with the majority living in Africa. While future conflict will be responsible for hundreds of millions of people living in poverty, its elimination is not a panacea for achieving development targets: even in a scenario with no intrastate conflict from 2022 to 2030 the population living in extreme poverty is projected to be 6.9%, well above the target threshold of 3% for achieving the first Sustainable Development Goal.

Defining ‘metropolitan’ poverty: Isolation gradients in major US urban areas

As suburban poverty has become more prevalent in recent years, low-income neighbourhoods have emerged outside of many central cities. In many regions, however, there remains a stark divide between the core city and outlying areas. Measuring poverty concentrations, therefore, depends on the choice of geographic scale. Widespread urban poverty results in low measures of poverty concentration inside core cities, and whether this increases or decreases once suburbs are considered depends on specific regional characteristics. This study calculates ‘isolation gradients’ for the population in poverty in the 50 largest US Metropolitan areas (MSAs), extending from the core city to beyond the MSA level. A variety of patterns emerge, including sharp increases in isolation scores outside the city (as in Detroit) as well as decreases (for Atlanta). An econometric analysis of the ratio of MSA-level to core-city isolation scores finds that, controlling for land area and core-city poverty rates, much of the variance is explained by per-capita income and differences in racial segregation. A comparison of gradients in 2000 and 2015–2019 for a subset of cities shows additional patterns of suburban and urban convergence and divergence.

A relational approach to the ethnographic study of power in the context of the city of London

The immersive ethnographic tradition has strong potential to contribute to a deeper sociological understanding of the construction, maintenance and processes of powerful groups. However, ethnography as a method – and sociology as a discipline – has tended to focus more on developing techniques and toolkits for studying what Bourdieu and Wacquant call a “poverty population” rather than elites systems of power. In response, this article builds a much needed ‘toolkit’ for would-be-ethnographers, examining how ethnographic methodologies can be adapted to critically examine the elite cultural fields. It does so by adapting Desmond’s four foci of relational ethnographic: fields, boundaries, processes and cultural conflict. Adopting a relational orientation, this article provides an illustration of how ethnography can be used in the study of powerful cultural fields, using the context of the City of London, and thereby forming the basis for future research.

Determinants of poverty in the US state of Virginia: an examination of the impact of rent (the neglected variable)

ABSTRACT This study provides new insight into factors that influence the poverty rate by testing the following hypothesis: the percentage of the population in poverty is positively related to rent levels. Rent levels constitute an issue effectively overlooked in the poverty determinants literature. The present study estimates a panel data set inclusive of control variables for the US state of Virginia, which provided all the data needed for the analysis. Panel least squares (PLS) estimations using county fixed effects and period fixed effects for the period 2008–17 find poverty inversely related to median income and the percentage of the population with at least a high-school diploma. Poverty also is found to be positively related to the percentage of the population employed in mining; the percentage of the population classified as obese; and the unemployment rate. Finally, poverty in Virginia is, as hypothesized here, an increasing function of rent. Higher monthly rental levels on one-bedroom apartments increase the percentage of the population in poverty; indeed, a US$100 per month increase in rent would elevate the overall poverty rate in the state by 1.20–1.35%.

Identifying community-level disparities in access to driver education and training: Toward a definition of driver training deserts

Objective Obtaining a license may be challenging for teens due to access to driving instruction; in some states, behind-the-wheel (BTW) instruction is required to secure a license before age 18. We investigate spatial accessibility to BTW centers, and how this geographic distribution intersects with metrics of social disparity at the metropolitan level, toward identifying Driver Training Deserts (DTDs): geographic areas of disconnection to driver training. Methods For the Columbus OH region, we collect socioeconomic variables at the Census tract unit of analysis and geocoded locations of public and private BTW training centers and estimate travel time to the nearest BTW training center. We define travel time as either the mean or the maximum travel time to BTW centers across all 1 km × 1 km grid cells within a Census tract. We employ spatial statistical approaches, including homogeneous/inhomogeneous K functions, to determine whether BTW training centers are clustered. Next, we define DTDs as Census tracts with a poverty rate and travel time to BTW centers larger than the 75th percentile values across the region. Results BTW training centers are spatially clustered across the region; the magnitude of this clustering is so great that BTW centers exhibit statistically significant patterns of clustering, even when considering the underlying spatial distribution of socio-economic characteristics. We find that 11–27 Census tracts are identified as DTDs depending on the definition of travel time. DTDs contain a disproportionate percent of the high poverty population (8.7–23.5%) and, depending on the definition of travel time, a disproportionately large African American population. Conclusions Methodologically, defining DTDs necessitates a fine-grained spatial approach as suburban and rural Census tracts tend to be large and thus can be poorly represented by travel times averaged over the Census tract. Defining DTDs as a measure of individual-specific variables – income and impedance – allows DTDs to be addressed with policy interventions. The findings motivate future research correlating DTDs with licensure rates, enrollment in driver training, and safe driving outcomes to understand if DTDs can help explain health equity outcomes related to young driver safety.

Solutions to prevent poverty-returning in the post-poverty era —— Social entrepreneurship research based on the perspectives of social capital, legitimacy and organizational driving force

As the phenomenon of China's out of poverty population falling into poverty again becomes more and more serious, how to fundamentally solve the problem of returning to poverty has received attention increasingly. Based on the perspectives of social capital, legitimacy and organizational driving force, this paper analyzes the high coupling of social entrepreneurship in solving the problem of poverty-returning, and the superiority of social enterprises over commercial enterprises, the governments and non-profit organizations under the issue of eliminating poverty-returning. It is concluded that social enterprise is the main body to solve the problem of returning to poverty, and social entrepreneurship is an effective means to solve the problem of returning to poverty.

Social-Geographical Patterns of Rescue Requests During Hurricane Harvey

We analyze a public dataset of rescue requests for the Houston Metropolitan Area during Hurricane Harvey (2017) from the Red Cross. This dataset contains information including the location, gender, and emergency description in each requester’s report. We reveal the spatial distribution of the rescue requests and its relationship with indicators of the social, physical, and built environment. We show that the rescue request rates are significantly higher in regions with higher percentages of children, male population, population in poverty, or people with limited English, in addition to regions with higher inundation rate or worse traffic condition during Hurricane Harvey. The rescue request rate is found to be statistically uncorrelated with the percentage of flood hazard zone designated by the Federal Emergency Management Agency (FEMA).

Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California.

Assessing exposure to fine particulate matter (PM2.5) across disadvantaged communities is understudied, and the air monitoring network is inadequate. We leveraged emerging low-cost sensors (PurpleAir) and engaged community residents to develop a community-based monitoring program across disadvantaged communities (high proportions of low-income and minority populations) in Southern California. We recruited 22 households from 8 communities to measure residential outdoor PM2.5 concentrations from June 2021 to December 2021. We identified the spatial and temporal patterns of PM2.5 measurements as well as the relationship between the total PM2.5 measurements and diesel PM emissions. We found that communities with a higher percentage of Hispanic and African American population and higher rates of unemployment, poverty, and housing burden were exposed to higher PM2.5 concentrations. The average PM2.5 concentrations in winter (25.8 µg/m3) were much higher compared with the summer concentrations (12.4 µg/m3). We also identified valuable hour-of-day and day-of-week patterns among disadvantaged communities. Our results suggest that the built environment can be targeted to reduce the exposure disparity. Integrating low-cost sensors into a citizen-science-based air monitoring program has promising applications to resolve monitoring disparity and capture “hotspots” to inform emission control and urban planning policies, thus improving exposure assessment and promoting environmental justice.

Ecological Environment and Poverty Governance Based on Deep Learning of Big Data

The ecological environment is the basic condition for human survival and development. Maintaining a good rural ecological environment is the basis for ensuring the sustainable development of agriculture and the rural economy, and it is the fundamental guarantee for helping poor rural areas to get rid of poverty and become rich. To solve poverty by developing tourism, the so-called tourism poverty alleviation has been studied for many years in the theoretical circles at home and abroad. Therefore, this article conducts research on China’s rural ecological environment management and poverty management based on big data deep learning, aiming to analyze the problems in China’s rural ecoenvironmental management and the challenges facing rural poverty governance and explore a way to achieve sustainable rural economic development and farmers’ poverty alleviation the best way. In the context of big data, environmental monitoring and governance have also ushered in innovative reforms. With the advantages of powerful information collection and data processing, big data provides comprehensive data and information support for environmental monitoring and governance. This article uses a survey method, data statistics method, literature analysis method, and case analysis method. Firstly, it briefly summarizes the main ecological and environmental problems and poverty management issues facing the rural areas of China. It then lists 5 successful poverty alleviation cases to investigate their poverty alleviation. The experience and methods of getting rich sum up the strategies that China can refer to for poverty alleviation. Finally, through the collection and compilation of online data, we have discovered the results achieved by China’s poverty alleviation work in recent years, i.e., by the end of 2019, our rural poverty population has been reduced to 5.1 million. Compared with 2013, there has been a reduction of approximately 90 million (Fang, 2019), however, at the same time, China’s poverty alleviation work has entered a stage of overcoming difficulties. The remaining poor people make it a long way to go. In short, improving the ecological environment to help rural poverty alleviation is a long-term people’s livelihood project, and it is also a research topic of great social significance. For this reason, the research in this article has a certain reference value.

Trends in rice research: 2030 and beyond

AbstractRice production and research have met unprecedented challenges in recent years. Yield and total production have plateaued for many years in some major producing rice‐producing countries while the demand from populations in poverty is ever increasing. For example, more than 100 million additional people became extremely poor, mostly from Asia and sub‐Saharan Africa in 2020 alone. Rice is not only the calorie source for half of the global population but also the key staple food for the world's poorest and undernourished people living in Asia and Africa. In this review, we have analysed the trends in rice research in the past three decades, particularly on the mega‐projects that attempted to revolutionize rice yield, sustainability and quality of both Asian (Oryza sativa) and African (O. glaberrima) rice, with their impact on rice cultivation. We have also analysed the trends in population growth, rice cultivation, production, price and consumption along with their projections for 2030 and beyond. Furthermore, we have analysed recent trends in variety release using Bangladesh as an example. Finally, we have identified the future challenges and priorities of rice research.

Application of Data Science for Cluster Analysis of COVID-19 Mortality According to Sociodemographic Factors at Municipal Level in Mexico

Mexico is among the five countries with the largest number of reported deaths from COVID-19 disease, and the mortality rates associated to infections are heterogeneous in the country due to structural factors concerning population. This study aims at the analysis of clusters related to mortality rate from COVID-19 at the municipal level in Mexico from the perspective of Data Science. In this sense, a new application is presented that uses a machine learning hybrid algorithm for generating clusters of municipalities with similar values of sociodemographic indicators and mortality rates. To provide a systematic framework, we applied an extension of the International Business Machines Corporation (IBM) methodology called Batch Foundation Methodology for Data Science (FMDS). For the study, 1,086,743 death certificates corresponding to the year 2020 were used, among other official data. As a result of the analysis, two key indicators related to mortality from COVID-19 at the municipal level were identified: one is population density and the other is percentage of population in poverty. Based on these indicators, 16 municipality clusters were determined. Among the main results of this research, it was found that clusters with high values of mortality rate had high values of population density and low poverty levels. In contrast, clusters with low density values and high poverty levels had low mortality rates. Finally, we think that the patterns found, expressed as municipality clusters with similar characteristics, can be useful for decision making by health authorities regarding disease prevention and control for reinforcing public health measures and optimizing resource distribution for reducing hospitalizations and mortality.

Energy and transport poverty amidst plenty: Exploring just transition, lived experiences and policy implications in Iceland

The concept of ‘just transitions’ holds that sociotechnical change should not be achieved at the expense of vulnerable social groups. Here we take the case of a country with a high level of primary energy share that is renewable – Iceland – as well as high living standards, showing how energy and transport poverty are both possible and precariously experienced. Although Iceland performs well in OECD terms with respect to the Gini index of income inequality, poverty is nonetheless systemically present. While the percentage of the population in poverty is small, for those individuals, the experience shapes their lives. Focusing on energy and transport poverty, we draw together analysis of Statistics Iceland data; focus groups with representative members of the Icelandic public; and interviews with people self-identifying as either having a disability or experiencing poverty. We take disability as an exemplar case of a vulnerable group. While none of our interviewees had experienced loss of access to heat in the home, some had experienced deliberate disconnection by power companies. All interviewees experienced transport-related difficulties in terms of cost or access, and the focus group participants provide details on the mixed experience of the more typical Icelander via a vis transport. The Icelandic case illustrates how welfare state benefit design and the general cost of living impact individuals' lived experience of transport and energy use in the home, despite energy supply being low carbon. We discuss corresponding policy and research implications.

Language Planning and Poverty Alleviation

This study examined the relationship between language planning and poverty alleviation. The purpose was to investigate the means of poverty alleviation via language planning. Three research questions guided the study. The study was exploratory in nature using empirical survey, which were analyzed empirically. Language planning in terms of education, according to the findings, is the cornerstone of economic growth, social development, and the primary way of enhancing individual wellbeing. It contributes to poverty reduction by enhancing the value and effectiveness of the poor's labour, as well as reducing the population, health, and nutritional effects of poverty. Language planning becomes ever more important as economies throughout the globe are altered by technology breakthroughs and new production processes that rely on a well-trained and intellectually adaptable workforce. Based on the above findings, there is need for more focus on language planning by the Nigerian government, by this I mean the language they can use in reaching out to the poor in order to alleviate the poverty situation of the country and for nation development.

The poverty evolution of typical countries along the Belt and Road and implications from China’s poverty reduction experiences

The world is facing a poverty crisis. Despite the great achievements that have been made in poverty alleviation over the past two decades, the extent of poverty in countries along the Belt and Road is still high. Successful poverty reduction in these countries is crucial to meeting the 2030 SDGs. Improving governance to eradicate poverty is a shortcoming that needs to be addressed urgently in poverty reduction pathways along the Belt and Road. In this study, the Standard Deviational Ellipse method was used to study the spatial trajectory of the poverty gravity center. Results showed that the poverty gravity center moved from east to west by 87.60 km annually, while the poverty population decreased by 1211.14 million along the Belt and Road from 2000 to 2020. In addition, the trajectory of the center has shifted due to the different effects of poverty reduction. Among the countries situated along the Belt and Road, China is the most significant contributor to poverty reduction. Accordingly, this study examined the implications of China’s successful poverty reduction strategies in order to understand how other countries can effectively respond to poverty. Ultimately, we propose that sustainable poverty alleviation development strategies should be established with the objectives of promoting social equity and improving the wellbeing of all people.

Statistical Measurement of the Overall Scale of Urban Poverty in China

As China is undergoing rapid urbanization and social transformation, the research on urban poverty has become increasingly important. So far, the Chinese government has still not drawn an official urban poverty line. The statistical measurement of the overall scale of urban poverty in China is carried out based on three aspects: price adjustment, income distribution data, and main poverty-stricken population, in which the trend analysis of the poor population, the maximum likelihood estimation, and the recent price adjustment are used as measures. The arithmetic average of the urban poverty population, measured via the above three different measures, is taken to obtain the current overall scale of urban poverty in China, which is 10.816 million.

The costs and constraints of pandemic response in Mali*

The costs and constraints of pandemic response in Mali*

Effects of Experiential Learning on Students’ Use of Facilitative Language Techniques during Shared Book Reading with Young Children

The purpose of this pilot study was to measure the effects of experiential learning on graduate students’ use of facilitative language techniques (FLTs) to support language development in young children from a high poverty population. Seven CSD graduate students who participated in a language seminar received direct instruction in and experiential learning with 11 FLTs. The students implemented the learned techniques during an 8-week experience in the community while providing shared book reading activities for children at a local family shelter. Results indicated that the students made significant gains in the number and type of FLTs used during book reading activities. The findings suggest that experiential learning yielded clinically significant changes in the graduate students’ use of FLTs during shared book reading with young children. Implications are provided for further research.

The Poverty Balancing Equation: Expressing Poverty of Place as a Population Process.

The accurate measurement of poverty is essential for the development of effective poverty policy. Unfortunately, approaches that use poverty rates to assess the causes and consequences of poverty do not fully capture the components of change in the poverty population because changes in the conventional poverty rate can occur owing to processes of natural increase, migration, or transitions in and out of poverty. This article presents an accounting framework for changes in poverty within and between places. The framework, termed the poverty balancing equation, generates a series of summary statistics that can be used in place of the conventional poverty rate in future research. The approach is demonstrated using the 2014 panel of the Survey of Income and Program Participation to generate state-level estimates of the poverty components of change for three states in the American South between January and December of 2013. Results show that even when poverty rates remain constant, there is significant dynamism within poor and nonpoor populations. By applying this approach, either completely or in part, researchers can provide more specific and actionable evidence for poverty alleviation policy.

Impacts of COVID-19 on public transit ridership

In this paper, a national-wide study is conducted to investigate the impacts of COVID-19 on the public transit ridership in the top twenty metropolitan areas in the U.S. At first, COVID-19 composite index was developed to qualitatively measure the level of public fear toward COVID-19 in different metropolitan areas. After that, to analyze the impact of COVID-19 and some socioeconomic factors on transit ridership reduction during the COVID-19 pandemic, a random-effects panel data model was developed and the traditional correlation analysis was also conducted. According to the results of both analyses, it was found that the areas with higher median household income, a higher percentage of the population with a Bachelor’s degree or higher, higher employment rate, and a higher percentage of the Asian population are more likely to have more reductions in public transit ridership during the COVID-19 pandemic. On the other side, the areas with a higher percentage of the population in poverty, and a higher percentage of the Hispanic population are more likely to experience smaller reductions in public transit ridership.

Poverty and energy issues as environmental and health challenges in SDGs

Abstract In 2019, 21.1 % of the EU-27 population were at risk of poverty or social exclusion. Energy poverty is one of many poverty forms and it is a widespread problem across Europe, as between 50 and 125 million people are unable to afford proper indoor thermal comfort. Energy poverty is linked to low household income, high energy costs and energy inefficient homes. These challenges are deeply connected with SDG7 and SDG1, and also produce environmental pollution. The roots of energy poverty are in polluting fuels that are the cheapest and at hand to the population in (risk of) poverty. Biomass heating is the inefficient use in old stoves and the lack of wood drying before use (the loss of up to 50% of the energy and higher energy costs of heating). Biomass and coal is also a major contributor to poor air quality in many European regions, especially in eastern part of the EU and Western Balkans. Biomass smoke contains health-damaging substances (particulate matter, PAHs etc). Studies on indoor air pollution show concentrations of PM10 may extremely exceed standards for ambient air pollution levels and put the people (mostly women and children), at increased risk of health impacts. Biomass burning also leads to the release of black carbon, which is not only a concern for health, but also as short-lived climate change forcer (SDG 13). A conservative estimate of the current contribution of biomass smoke to premature mortality in Europe amounts to at least 40,000 deaths per year. The inefficient use of the biomass means higher costs for already ‘disadvantaged' citizens and those in risk of (energy) poverty. Energy poverty is a distinct form of poverty associated with a range of adverse consequences for people's health and wellbeing (respiratory diseases, CVD, mental health, and stress associated with unaffordable energy bills). Poverty and energy issues as environmental and health challenges should seen through SDG 1 and SDG 7, but also through SDG 8, SDG1 1 and SD G3.