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What are the consequences of upward socioeconomic mobility for disenfranchised individuals? This article examines this question in the context of a business training program offered to residents of Brazilian urban slums, known as "favelas." The study employs a randomized controlled trial complemented by quantile regressions, field visits, and interviews. The results show that training improves favela dwellers' economic outcomes, such as by increasing income and participation in entrepreneurship, and some socio-psychological outcomes, such as by improving self-efficacy and optimism. However, these income improvements were accompanied by participants' enhanced experiences of favela stigma, an adverse socio-psychological outcome related to their residential segregation. Both quantitative and qualitative findings demonstrate the multifaceted nature of socioeconomic mobility, through which favela dwellers who prosper economically become more exposed to prejudice from people living outside favelas. The study illustrates, through the "allegory of the favela," the bittersweet process of socioeconomic mobility. This abductive research contributes to the literature by showing that while interventions designed to enfranchise individuals may effectively achieve economic inclusion in terms of income gains, they may simultaneously lead participants into discriminatory systems that further stigmatize people based on the same characteristics of their prior exclusion. [ABSTRACT FROM AUTHOR]

Organisations are having difficulty in determining and integrating Industry 4.0 technologies (I4.0T) to improve social dimensions of sustainable performance. We address this issue by showing how to identify the impact degree and path of I4.0T using the United Nations sustainable development goals (SDGs). First, we identify the SDGs associated with I4.0 and establish an evaluation framework. Second, we introduce an evaluation method that integrates hesitant fuzzy sets, rough sets, decision-making, trial evaluation laboratory (DEMATEL) and interpretative structural modelling methods to identify the impact degree and path of I4.0T on SDGs. Third, we confirm the effectiveness of our framework and method using secondary case data from World Economic Forum reports. The case results show that I4.0T have varying direct and indirect influences on SDGs. Policy makers should consider that 'Big Data and Analytics' and 'Cloud Computing' are central I4.0T that link other technologies and SDGs. The prioritisation of I4.0T can lead to contributions to addressing 'Responsible consumption and production' and indirectly improve SDGs. The findings set an initial stage to help sequence investment in various technologies depending on SDGs. We identify sequential paths that can aid in planning for and investing in adopting I4.0T to better achieve SDGs. [ABSTRACT FROM AUTHOR]

Abstract: Accurate, inexpensive and granular human poverty assessments are critical for data-driven policy decision-making. This research proposes a novel approach to computing poverty scores utilizing multispectral satellite images and indices calculated from census reference values. We show how this approach can leverage standard and sparse survey-based multidimensional poverty assessments at the municipal level to develop a deep learning architecture to obtain poverty scores at the residential block level. This method has the distinctive feature that the obtained inference corresponds to Multidimensional Measurement of Poverty generated by CONEVAL, the Mexican agency responsible for measuring poverty. We provide a reliable alternative to survey-based approaches with an $$R^2$$ R 2 of $$0.802\pm 0.022$$ 0.802 ± 0.022 for the lack of housing quality and spaces dimension. A convolutional neural network trained on multispectral satellite images and the lack of housing quality and spaces dimension, which is regressed from census reference variables corresponding to lack of water, electricity, sewage, concrete floor, toilet and occupancy level obtains an $$R^2$$ R 2 of 0.753. These results represent a significant step forward in including machine learning techniques to provide reliable information at reduced costs and a higher spatiotemporal frequency than traditional person-to-person surveys.

Accurate assessments of global primary material extraction, trade of primary materials and products, material use, waste, and emissions support the development of policies that facilitate the decoupling of economic activity, natural resource use, and related environmental impacts. Here, we quantify all crucial aspects of global and country‐by‐country material requirements needed to fuel economic activities, covering both territorial‐ and demand‐based indicators. These data have been assembled by a consortium of research partners that compile the global material flow and resource productivity online database for the International Resource Panel, which contributes to the global dataset for the System of Environmental–Economic Accounting (SEEA) framework and is employed to monitor progress for the Sustainable Development Goal (SDG) indicators 8.4 and 12.2. We present the main findings of the 2024 update, including methodological improvements and result differences, and discuss the main findings and limitations. Since the last update, we have identified a slowing of global materials extraction since about 2014, a continuation of solid growth in direct trade of materials and products, persistent inequality in resource use between high‐ and low‐income countries, and a prolonged improvement in global material productivity. The full dataset used herein can be downloaded from the Global Material Flow Database hosted by the United Nations Environment Program International Resource Panel. [ABSTRACT FROM AUTHOR]

A burgeoning population, food shortage, less affordability of essential nutrients, and pandemic are the foremost global challenges for lower-to middle-income nations. Lack of proper availability of crucial nutrients leads to hidden hunger, which has become a serious threat under the current scenario and difficult situation for global policymakers, nutritionists, and public health scientists. Minerals (iron, zinc, iodine, and Selenium) and Vitamin A malnutrition are major food-related primary health problems among populations of both developed and developing countries. Vegetables offer an economical and sustainable opportunity to provide micronutrients. They are rich in minerals, vitamins, and bioactive compounds and thus play a key role in diversifying diets and securing nutritional security. Usually, the availability of most micronutrients in the edible parts of the plants is lower than required. Therefore, scaling up the nutritional profile of vegetable crops through biofortification can enhance their nourishment power. Biofortification can be achieved through mineral fertilization, breeding, and biotechnological approaches. Several crops have been fortified through the soil and foliar application of fertilizers, thus providing benefits for a limited period. Therefore, breeding for nutrient-rich cultivars using conventional or biotechnological techniques seems to be the most effective strategy to reduce malnutrition. [ABSTRACT FROM AUTHOR]

This study examines the linkages between regional integration, poverty, and inequality reduction in the South African Customs Union. This was achieved by applying an econometric analytical technique to panel data on the five-member countries covering 2000–17. Results confirmed that regional integration is important in poverty and inequality reduction. This study has revealed that poverty can be reduced by increasing the levels of integration with other economies, increasing Human Development Indexfst and reducing inequalities. Therefore, these findings show that SACU governments’ commitment to enhancing each of these variables is critical in achieving zero or reduced poverty among member states. [ABSTRACT FROM AUTHOR]

The study aims to examine the relationship between Sustainable Development Goals (SDGs) knowledge, sustainability attitudes, sustainable entrepreneurship, and sustainable behaviors among students enrolled in business-related courses at Spanish universities. Employing the Knowledge-Attitude-Behavior (KAB) model, this study innovatively disaggregates the attitude variable into attitudes toward sustainability and sustainable entrepreneurship. The findings affirm the direct and indirect effects posited in the model, indicating that familiarity with SDGs positively impacts attitudes toward sustainability, subsequently influencing sustainable behaviors. Moreover, positive attitudes toward sustainable entrepreneurship also directly influence sustainable behaviors. Additionally, the study examines the moderating influence of receiving a scholarship; results indicate that attitudes toward sustainability and sustainable entrepreneurship significantly shape behavior, with the scholarship variable altering the relationship between attitudes toward entrepreneurship and behavior. These outcomes underscore the significance of enhancing SDGs awareness and nurturing favorable attitudes toward sustainability and sustainable entrepreneurship among university students to stimulate sustainable behaviors and advance SDGs objectives. [ABSTRACT FROM AUTHOR]

Since the end of the Second World War, many countries have provided external assistance for Africa's growth and development. The impact of these funds on the achievement of the 2030 Sustainable Development Goals(SDGs) by African countries is not yet clear. This paper try to fill this gap by analyzing the impact of US aid on sustainable development goals in Africa. Based on data from 47 African countries for 2015 to 2020, this paper used fixed effect and ordered probit models to examine the impact of US aid on the achievement of Africa's SDGs. The results are as follows. First, United States aid to Africa is beneficial to improving the overall SDG scores of African countries. Second, United States aid to Africa contributes to the achievement of some of the SDGs in the social and economic and environmental dimensions. This is reflected in the positive impact on the scores of SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-Being), SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), SDG 15 (Life on Land). Third, United States aid to Africa has been instrumental in increasing the pace of achievement of some of the SDGs. This is reflected on the trend of changes in the scores for SDG 7 (Affordable and Clean Energy), SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation and Infrastructure), SDG l0 (Reduced Inequalities), SDG 11 (Sustainable Cities and Communities) and SDG 12 (Responsible Consumption and Production). Fourth, this paper further classify the forms of funding and find that the United States should increase funding for project support aid. Therefore, increasing aid for environmental protection and project support would be conducive to advancing the SDGs of African countries. [ABSTRACT FROM AUTHOR]

This research paper aims to explore a network governance in sustainable apiculture management and identify its challenges to government and non-governmental policy makers. Qualitative data was collected through participant observation during field visits and Focus Group Discussions (FGDs) with regional apiculture management. The research results show that each country in the Mekong subregion has different network governances in supporting a sustainable apiculture management. Some countries have a collaborative network between the government, the civil society, entrepreneurs, and scholars. In contrary, some countries lack a policy framework from the government. This difference becomes challenges for the six governments of the Mekong subregion countries to commonly support the sustainable apiculture management in the subregion. The identified challenges in the paper are: (1) a capacity gap between the six countries of the region; (2) no common policies and regulations that would facilitate local beekeepers' access to wider regional bee products; (3) no support for inter-regional transport of bees and honey for academic purposes; (4) inadequate native bee species preservation and pesticides use; (5) local beekeepers' limited access to a regional bee diseases and pesticides use database; and, (6) a lack of regional standards for general honeybee product support. [ABSTRACT FROM AUTHOR]

This narrative review explores the intersection of computational intelligence (CI) techniques and the Sustainable Development Goals (SDGs) in the context of female cancer patients. With the increasing prevalence of cancer among women worldwide, there is a pressing need to integrate advanced computational methods to enhance diagnosis, treatment, and management. This review highlights various CI methods, including artificial intelligence, machine learning and data science, and examines their contributions to achieving specific SDGs like health and well-being (SDG 3), gender parity (SDG 5), and reduced disparity (SDG 10). Additionally, the review considers the impact of CI on other relevant SDGs, such as poverty eradication (SDG 1), quality education (SDG 4), economic growth and decent work (SDG 8), innovation and infrastructure (SDG 9), and global partnerships (SDG 17). The paper discusses the current state of CI applications in female cancer care, identifies challenges, and proposes future directions for research and practice. [ABSTRACT FROM AUTHOR]