Search Results (4,234)

This research draws from participant interviews at baseline, midpoint, and conclusion of a two-year Basic Income program designed to lift 76 families, with at least one child under the age of six, above the California poverty line by supplying a guaranteed monthly cash stipend (average: $1289 per month). Theoretically, we bring the Family Stress Model into the conversation with the Theory of Change that underpins Guaranteed Income programming, namely that freedom and choice empower families to mitigate stress, manage funding, and better navigate the multifactorial aspects of living in poverty. Participants report that the Basic Income program offered a much-appreciated reprieve from poverty and reported using the funds to stabilize their housing and support the health and development of themselves and their children. Participants also highlighted how guaranteed cash programming can pair with traditional social service case management to better benefit recipients. Full article

Promoting resilience, increasing productivity and sustainability, and profit maximization remain key challenges facing farmers globally. These are exacerbated by factors such as climate change, low to no access to technological advancement, financial constraints, poor technical and management skills, inadequate government support, and limited access to resources. However, there are diverse strategies that abound, including on-farm diversification, that farmers could leverage on to address these numerous and complex challenges. This study investigated the determinants of on-farm diversification strategies among smallholders in Mpumalanga Province. The study employed a quantitative approach using closed-ended survey questionnaires to elicit information from a total of 465 farmers who were randomly sampled from a total population of 14,411. The data gathered were analysed using descriptive statistics to determine the on-farm diversification strategies employed by farmers and the factors influencing the use of these strategies. A binary logistic regression model was employed to establish the relationship between on-farm diversification strategies and the determining factors. More than half of the farmers were female (51.8%), with only 48.2% male. The majority (59.1%) of the farmers were between the ages of 36 and 60, with only 20.2% youth participation in farming. Slightly more than half (50.8%) of the farmers practise mixed farming as their on-farm diversification strategy, while only 4.3% of the farmers practise mono-cropping. The study identified significant variables such as level of education (p = 0.001), secondary source of income (p = 0.057), farmland size (p = 0.022), number of farm assistants (p = 0.016), and on-farm diversification awareness as key determinants of on-farm diversification among smallholder farmers in Mpumalanga Province. Therefore, it is recommended that policies within the agricultural sector be revised to encourage on-farm diversification in order to motivate farmers to transition to agripreneurship for poverty alleviation, food security and rural economic development (RED). Full article

Childhood stunting remains a major public health challenge in India and is influenced by multiple socioeconomic and environmental factors. This ecological study examined district-level correlates of childhood stunting, including Crimes Against Women (CAW), the Multidimensional Poverty Index (MPI), and drought severity, using data from NFHS-5, the National Crime Records Bureau, NITI Aayog’s MPI reports, and the Drought Atlas of India. Spatial autocorrelation and Spatial regression models were applied alongside machine learning approaches and SHAP-based Explainable AI (XAI) interpretation. Childhood stunting exhibited significant spatial clustering (Moran’s I = 0.520, p < 0.001), with hotspots in northern, central, and eastern India. Higher stunting was associated with higher birth order, low maternal BMI, child anaemia, and MPI, and negative associations with iodised salt usage, electricity access, and timely postnatal care. A significant spatial lag parameter (ρ = 0.348) indicated substantial spillover effects. Machine learning models consistently identified MPI, drought severity, and CAW as key predictors. The integrated spatial and machine learning framework identifies key correlates and spatial dependencies of childhood stunting, highlighting the need for region-specific, multisectoral interventions. Full article

In the context of rural sustainability and poverty alleviation within the developing world, a key dilemma facing the international community is to identify suitable strategies and mechanisms to bring multiple stakeholders together to work in efficient and sustainable ways. This paper focuses on the Public–Private–Producer Partnership (4P), a model that involves cooperation between government agencies, business firms, and small-scale producers to foster mutual trust and enhance collaboration through infrastructure development and capacity building in the agricultural value chain. Drawing on evidence from China, Indonesia, Rwanda, Ghana, and Nigeria, this study examines the impact of 4P on crop productivity, agricultural infrastructure, market access, stakeholder empowerment, employment, the land tenure system, and household income. This paper combines value chain analysis, Theory of Change mapping, and both qualitative and quantitative evaluation techniques to assess how the 4P model functions in different institutional and ecological contexts. While the model promotes inclusive growth, it also faces challenges such as price volatility, insufficient long-term sustainability, and limited integration of smallholder farmers into formal value chains. The paper discusses policy implications for improving the 4P model’s effectiveness in poverty alleviation and local economic development, highlighting the importance of better governance structures, financial mechanisms, and market stability. This paper sheds new light on inclusive, justified, and sustainable collaboration mechanisms for participatory agencies and individuals. Full article

This study investigates the effect of digital financial inclusion on both inclusive growth and poverty in Emerging and Developing Economies (EMDEs). While previous research has examined the relationship between digital financial inclusion and inclusive growth or poverty, there is a notable gap in the literature regarding the indirect effect of digital financial inclusion on poverty through inclusive growth. Additionally, many existing studies have focused on specific countries, leaving a need for a cross-sectional analysis across various EMDEs, particularly in under-researched regions such as Central Africa, Southern Africa, West Africa, Oceania, and South-Eastern Europe. To address these gaps, this research employs panel data and the System-Generalized Method of Moments (GMM) as the main estimation technique, which provides robust and efficient estimates while addressing potential endogeneity. The study constructs a new digital financial inclusion index using the Principal Component Analysis (PCA) approach to enable consistent cross-country comparisons. The findings reveal that digital financial inclusion has a positive and significant effect on inclusive growth, indicating that as digital financial inclusion increases, inclusive growth increases as well. The results also demonstrate that inclusive growth has a negative and significant effect on poverty, suggesting that equitable economic expansion is a key driver of poverty reduction. These findings provide policymakers and governments in EMDEs with valuable insights, helping them prioritize investments and strategies that leverage digital financial inclusion to foster inclusive growth and alleviate poverty. Full article

Background/Objectives: The purpose of this article (a comparative analysis of state laws) is to thoroughly examine enacted state-level healthy universal school meals bills to summarize bill content and determine current practices for program implementation and long-term viability, with special attention to the Community Eligibility Provision (CEP). Methods: Bills enacted at the state level, as of 31 December 2025, were located electronically on state legislature websites and subsequently reviewed with rules, regulations, and implementation guidelines. Content analyses were conducted to identify patterns, themes, and key concepts pertaining to healthy universal school meals laws and program implementation guidelines to inform comparison policy analyses. Results: Nine states (California, Colorado, Maine, Massachusetts, Michigan, Minnesota, New Mexico, New York, and Vermont) have healthy universal school meals laws that include mandatory funding provisions for programming. Michigan is the only state that has a non-permanent law. Such laws eliminate requirements to certify individual students for free, reduced-price, or full-price meals based on their household income, and instead allow entire schools and/or school districts to offer all enrolled students no-cost meals. All states are funding healthy universal school meals programming by leveraging existing or new tax revenue to bridge the gap between the cost of school meals and federal meal reimbursements. Conclusions: State laws that leverage the Community Eligibility Provision (CEP) have become a key way to sustain universal school meal programs when federal funding falls short. States that direct resources to high-poverty schools, help districts determine the most accurate Identified Student Percentage, and reduce undercounting through strong direct-certification practices are better positioned to maintain universal meals over time. These strategies strengthen both child health and academic outcomes by ensuring stable access to no-cost, nutritious meals. Full article

Countries around the world are committed to achieving the Sustainable Development Goals (SDGs). However, significant challenges remain—particularly the economic consequences of climate change. Using a GVAR model for 17 economies over the period 2001M1–2021M12, we explore how temperature anomalies affect industrial production through four potential mechanisms: food prices, credit costs, exchange rates and investment. Our theoretical model demonstrates that temperature anomalies lower agricultural production, which drives up food prices and reduces real wages. This in turn leads to lower investment and production in the industrial sector. Our empirical results indicate that rising temperature anomalies are associated with a decrease in industrial production and investment, as well as the depreciation of domestic currencies relative to the U.S. dollar. Additionally, we observe that the influence of temperature anomalies is more pronounced in hot regions than in cold regions. Our investigation underscores the importance of financial markets and investment as potential transmission channels for the impact of climate change on industrial production. This study provides empirical evidence to support policymaking aimed at mitigating the adverse impacts of climate change, thereby helping countries to advance toward key SDGs such as no poverty, zero hunger, and climate action. Full article

We assess associations between emergency room (ER) visits, scaled to per 10⁵ population per year, for asthma and chronic obstructive pulmonary disease (COPD), two of the most common respiratory diseases, and zip code-level exposure to criteria air pollutants (CAPs) coming from point sources in New York State (NYS) from 2010 to 2018. Exposure data on point source CAPs were retrieved from the United States Environmental Protection Agency (USEPA) National Emission Inventory (NEI) database, and ER visits for asthma and COPD were acquired from the New York State Department of Health (NYSDOH) Statewide Planning and Research Cooperative System (SPARCS). To account for within-county variability, we used log-linear mixed effects models, adjusted for year, sex, age category, county-level poverty, smoking, PM_2.5, volatile organic compounds (VOCs), and CAPs sources within the study period. Results show significant associations between ER visits for asthma and COPD and most of the pollutants in the study, even after adjusting for the effects of poverty and smoking. Although point source emissions comprise a small portion of total air pollution, our findings show that zip code-level point source CAPs, especially the gaseous pollutants, pose a modest but significant contribution to the risk of respiratory disease-related ER visits. Full article

Coffee, as a perennial commodity crop, plays a crucial role in global agricultural markets, regional livelihoods, and poverty alleviation. Yunnan Province of China (21°8′–29°15′N) represents the northernmost coffee-growing region worldwide, and its production has gained increasing attention in international markets. However, the absence of a spatially explicit and high-resolution coffee distribution dataset has constrained environmental assessment, land-use analysis, and policy-making in this subtropical and marginal growing region. In this study, we developed the first 10 m resolution Arabica coffee distribution dataset for Yunnan Province for the year 2023 using Sentinel-2 optical imagery and Shuttle Radar Topographic Mission (SRTM) terrain data within the Google Earth Engine (GEE) platform. An object-based workflow was implemented to generate spatially coherent mapping units, followed by supervised classification to identify coffee plantations. The resulting map achieved an overall accuracy (OA) of 0.87, with user accuracy (UA), producer accuracy (PA), and F1 score of 0.90, 0.96, and 0.93 for the coffee class, demonstrating its reliability for regional-scale applications. Feature contribution analysis indicates that shortwave infrared (SWIR) and red-edge information, particularly during the dry season, plays an important role in coffee discrimination. These results enhance confidence in the ecological relevance and stability of the mapping framework. The proposed workflow provides a practical and transferable approach for perennial crop mapping in complex mountainous environments. More importantly, the generated high-resolution coffee distribution dataset establishes a spatial baseline for monitoring land-use dynamics, assessing ecological impacts, and supporting sustainable coffee development in southwestern China. Full article

Energy poverty remains an important challenge for sustainable development in China, with pronounced regional disparities and evolving temporal dynamics that require accurate and interpretable prediction tools. This study develops a provincial panel-based framework that combines Energy Poverty Index (EPI) construction, SSA-LSTM prediction, SHAP-based model interpretation, and two-way fixed effects (TWFE) regression analysis. Using provincial data for China (2003–2022), we first construct a composite EPI with the entropy weight method, then apply a Sparrow Search Algorithm (SSA) to optimize LSTM hyperparameters for EPI forecasting. SHAP is used to interpret feature contributions to model-predicted EPI, and TWFE regression is used to provide complementary panel-data evidence on factor–EPI associations. The results show that the SSA-LSTM model outperforms benchmark machine learning and deep learning models in out-of-sample prediction performance. SHAP-based interpretation indicates that variables such as GDP, energy intensity, and power generation per capita contribute strongly to prediction variation, with notable regional heterogeneity. TWFE results are broadly consistent with several key patterns identified in the SHAP analysis. Overall, the proposed framework provides an accurate and interpretable provincial energy poverty prediction approach and offers a useful empirical reference for energy poverty monitoring and policy discussion. Full article

This paper examines migration from Africa as a response to shifting identities and the resurgence of nationalism, bringing biblical traditions into dialogue with contemporary realities. In many African contexts, contested identities, ethno-religious nationalism, and exclusionary state policies intensify conditions of displacement alongside poverty, conflict, and terrorism. As a result, migration becomes both a survival strategy and a negotiation of identity in an increasingly fragmented world. Biblical narratives of forced migration provide an interpretive framework for understanding these movements. The Hebrew Bible recounts exilic experiences, such as the Babylonian deportation, that reshaped Israel’s communal memory, identity, and theology. Similarly, the New Testament highlights dispersions caused by persecution, showing how migration functioned as a catalyst for the expansion of faith communities and the reconstruction of belonging. These texts illuminate how forced migration is not only a consequence of crisis but also a transformative process that redefines identity and community. By employing sociological and theological methods, this study demonstrates how African migration in the context of nationalism parallels biblical paradigms of exile and dispersion. It argues that African migrants’ narratives of identity, marked by struggle, hope, and resilience, echo biblical testimonies of displacement and offer theological resources for interpreting migration today. In doing so, this paper contributes to interdisciplinary debates on migration by showing how biblical exilic traditions can inform responses to Africa’s ongoing challenges of nationalism, identity, and forced movement. Full article

In collaboration with various stakeholders, including learners, parents, teachers, district administrators, and community organizations, school social workers (SSWs) can positively influence the school ethos, reduce risks and barriers to learning, and increase learners’ resilience. This collaboration is particularly crucial in low- and middle-income countries, where psychosocial well-being support structures are lacking, significantly affecting learners’ well-being. This exploratory qualitative study aimed to explore the nature of collaboration in the practice of school social work in South African public schools in Gauteng province. Semi-structured interviews were conducted with 17 SSWs who provided informed consent. Reflexive thematic analysis confirms that SSWs actively promote and participate in interdisciplinary and inter-organizational collaboration to support learners. These collaborations were crucial for addressing complex issues such as child protection, substance abuse, mental health, and poverty. However, the identified challenges include limited participation by experts, key stakeholders, and parents, as well as poor coordination between the social development and education departments. These challenges hinder SSWs’ ability to address learners’ diverse needs effectively. Therefore, the study argues for a shift toward more formalized, uniform partnerships and proposes operational strategies to strengthen collaboration and the practice of school social work within the broader school system. Full article

This paper presents qualitative findings from a broader study conducted with beneficiaries of social assistance grants in Nkonkobe Municipality, South Africa, guided by Amartya Sen’s Capability Approach and a Feminist Political Economy perspective. It specifically examines the impact of the Child Support Grant (CSG) on women residing in rural areas with limited economic opportunities. Drawing on the narratives of twenty-five female beneficiaries, the study explores the grant’s role beyond child welfare outcomes. Despite its small monetary value, the CSG demonstrated significant and unintended transformative effects. Within contexts of persistent poverty, unemployment, and inequality, the grant contributed to alleviating household hardship and enhancing women’s empowerment. Participants reported increased economic agency, autonomy, and decision-making capacity. The CSG also served as a critical resource for women seeking to exit abusive relationships by providing a measure of financial independence, often lacking among survivors of domestic violence. These findings contribute to broader debates on welfare services as tools for equality, diversity, and democracy, highlighting the CSG’s potential to advance gender empowerment and social inclusion. However, the grant alone remains insufficient to ensure sustainable economic security. The paper recommends that the CSG be strengthened through increased value and complemented by active labour market interventions that promote women’s economic participation. Full article

Population aging and climate change are two long-term processes that increasingly intersect, yet their interrelationship remains insufficiently explored in Southeast Europe. This article examines how adults aged 50+ in Serbia and Bulgaria understand, perceive, and respond to climate risks, with the aim of identifying age-specific vulnerabilities as well as opportunities for climate action. We administered the ClimateMind50+ questionnaire to purposive national samples comprising 309 respondents in Serbia (CAPI, 82 municipalities) and 155 respondents in Bulgaria (CAWI, 74 municipalities). Socio-demographic differences were analyzed using descriptive statistics and χ² tests. The findings indicate moderate levels of self-assessed climate literacy, strong concern about the impacts of climate change on future generations, and heightened anxiety regarding extreme heat and prolonged dry periods. During climate-related emergencies, respondents rely predominantly on family networks rather than local institutions, and overall preparedness for extreme events remains limited. Adaptive and pro-environmental behaviors are modest and vary by gender, education level, and type of settlement. Population aging interacts with socio-economic vulnerability, energy poverty, regional decline, and governance constraints, shaping both exposure to climate risks and the capacity for behavioral adaptation. Climate strategies in both countries should therefore become more age-inclusive and socially responsive, recognizing older adults not only as a vulnerable group but also as active contributors to resilience. Full article

This study evaluates the costs and benefits of participatory forest management (PFM) versus non-participatory forest management based on the perceptions and involvement of local communities in the Kilombero Valley Ramsar site, Tanzania. The area hosts ecologically significant wetlands managed through different regimes: forests managed by local communities under PFM and protected areas controlled by national authorities. Using data collected through focus groups, key interviews, household surveys, and direct observations in two villages—Siginali (PFM) and Kilama (non-participatory)—this research explores perceptions of two different forest management approaches. The results revealed: (i) a generally low awareness and participation in forest management activities in both villages; (ii) restrictions on forest resource access, essential for local livelihoods, were common and often poorly accepted in the two villages; (iii) neither approach alleviates poverty, instead, strict regulations have worsened livelihoods by eliminating traditional income sources; (iv) forced participation in patrols and fire control was also noted as an unfair burden without direct compensation; and (v) the “fortress” model is perceived as more effective at improving forest health and stopping illegal activity due to stricter patrols. The study concludes that while PFM supports forest sustainability, it needs enhanced local engagement, benefit-sharing mechanisms, and complementary income-generating initiatives such as ecotourism to sustainably balance conservation and community welfare. Full article