Publication: Living on the Edge : Risk, Protection, Behavior, and Outcomes of Argentine Youth
Loading...
Date
2008-01
ISSN
Published
2008-01
Author(s)
Editor(s)
Abstract
Risk and protective factors influence behaviors and outcomes for youth. While risk factors expose youth to risk-taking behavior that compromises well-being and hinders personal development, protective factors mediate risk and act as protective mechanisms that insulate youth from negative outcomes. This paper groups youth by risk levels using a cluster analysis methodology, and identifies the risk and protective factors that characterize these groups. Using data from a new household survey covering youth in four urban areas of Argentina in 2005, youth are clustered by characteristics in relation to family and health, education and income, substance abuse, and crime and violence as indicators of risk and protective factors, and behaviors and consequences. Almost half of Argentine youth are at an elevated risk level, and one in four is at serious risk of experiencing negative outcomes or already suffering the consequences. The findings show, for example, that higher income protects against risk factors, such as an insecure neighborhood, and facilitates youth attending school. Furthermore, parents' lack of education is negatively related to the behaviors and outcomes of their children.
Link to Data Set
Citation
“Justesen, Michael. 2008. Living on the Edge : Risk, Protection, Behavior, and Outcomes of Argentine Youth. Policy Research Working Paper; No. 4485. © World Bank. http://hdl.handle.net/10986/6490 License: CC BY 3.0 IGO.”
Associated URLs
Associated content
Other publications in this report series
Publication Dynamic, High-Resolution Wealth Measurement in Data-Scarce Environments(Washington, DC: World Bank, 2025-02-06)Accurate and comprehensive measurement of household livelihoods is critical for monitoring progress toward poverty alleviation and targeting social assistance programs for those who most need it. However, the high cost of traditional data collection has historically made comprehensive measurement a difficult task. This paper evaluates alternative satellite-based deep learning approaches using detailed household census extracts from four African countries to accelerate progress toward comprehensive, fine-scale, and dynamic measurement of asset wealth at scale. The results indicate that transformer architectures solve multiple open measurement problems, by providing the most accurate measurement of local-level variation in household asset wealth across countries and cities, as well as changes in household asset wealth over time. Experiments that artificially restrict data availability show the model’s ability to achieve high performance with limited data. The proposed approach demonstrates the promise of combining satellite imagery, publicly available geo-features, and new deep learning architectures for hyperlocal and dynamic measurement of wealth in data-scarce environments.Publication Firm-Level Climate Change Adaptation(Washington, DC: World Bank, 2025-03-10)Are firms adapting to climate change? This paper studies this question by combining geocoded World Bank Enterprise Survey data with spatially granular weather data to estimate temperature response functions for nearly 160,000 firms in 134 countries over a 15-year period. Our results show that market imperfections in low- and middle-income countries constrain firms’ ability to adapt. Small and medium-size firms in low- and low-middle income countries are most vulnerable, with revenues declining by 12 percent in years with temperatures 0.5◦C above historical averages. The impact is equally strong for manufacturing and services firms and result from declines in labor productivity and wages. Heat-sensitive sectors and less resilient firms are more severely affected, reinforcing the causal interpretation. Unique firm-level information on policy constraints including limited financing, burdensome regulations, and unsafe conditions suggest that such factors raise adaptation costs, undermining economic resilience to climate change.Publication Beyond the AI Divide(Washington, DC: World Bank, 2025-02-24)This paper examines global disparities in artificial intelligence preparedness, using the 2023 Artificial Intelligence Preparedness Index developed by the International Monetary Fund alongside the multidimensional Economic Complexity Index. The proposed methodology identifies both global and local overperformers by comparing actual artificial intelligence readiness scores to predictions based on economic complexity, offering a comprehensive assessment of national artificial intelligence capabilities. The findings highlight the varying significance of regulation and ethics frameworks, digital infrastructure, as well as human capital and labor market development in driving artificial intelligence overperformance across different income levels. Through case studies, including Singapore, Northern Europe, Malaysia, Kazakhstan, Ghana, Rwanda, and emerging demographic giants like China and India, the analysis illustrates how even resource-constrained nations can achieve substantial artificial intelligence advancements through strategic investments and coherent policies. The study underscores the need for offering actionable insights to foster peer learning and knowledge-sharing among countries. It concludes with recommendations for improving artificial intelligence preparedness metrics and calls for future research to incorporate cognitive and cultural dimensions into readiness frameworks.Publication Indigenous peoples, land and conflict in Mindanao, Philippines(Washington, DC: World Bank, 2024-02-12)This article explores the links between conflict, land and indigenous peoples in several regions of Mindano, the Philippines, notorious for their levels of poverty and conflict. The analysis takes advantage of the unprecedented concurrence of data from the most recent, 2020, census; an independent conflict data monitor for Mindanao; and administrative sources on ancestral land titling for indigenous peoples in the Philippines. While evidence elsewhere compellingly links land titling with conflict reduction, a more nuanced story emerges in the Philippines. Conflicts, including land- and resource-related conflicts, are generally less likely in districts (barangays) with higher shares of indigenous peoples. Ancestral domain areas also have a lower likelihood for general conflict but a higher likelihood for land-related conflict. Ancestral domains titling does not automatically solve land-related conflicts. When administrative delays take place (from cumbersome bureaucratic processes, insufficient resources and weak institutional capacity), titling processes may lead to sustained, rather than decreased, conflict.Publication Who on Earth Is Using Generative AI ?(Washington, DC: World Bank, 2024-08-22)Leveraging unconventional data, including website traffic data and Google Trends, this paper unveils the real-time usage patterns of generative artificial intelligence tools by individuals across countries. The paper also examines country-level factors driving the uptake and early impacts of generative artificial intelligence on online activities. As of March 2024, the top 40 generative artificial intelligence tools attract nearly 3 billion visits per month from hundreds of millions of users. ChatGPT alone commanded 82.5 percent of the traffic, yet reaching only one-eightieth of Google’s monthly visits. Generative artificial intelligence users skew young, highly educated, and male, particularly for video generation tools, with usage patterns strongly indicating productivity-related activities. Generative artificial intelligence has achieved unprecedentedly rapid global diffusion, reaching almost all economies worldwide within 16 months of ChatGPT’s release. Middle-income economies have disproportionately high adoption of generative artificial intelligence relative to their economic scale, now contribute more than 50 percent of global traffic, while low-income economies contribute less than 1 percent. Regression analysis reveals that income level, share of youth population, digital infrastructure, specialization in high-skill tradable services, English proficiency, and human capital are strongly correlated with higher uptake of generative artificial intelligence. The paper also documents disruptions in online traffic patterns and emphasizes the need for targeted investments in digital infrastructure and skills development to harness the full potential of artificial intelligence.
Journal
Journal Volume
Journal Issue
Citations
Collections
Related items
Showing items related by metadata.
Error: Could not load results for 'https://openknowledge.worldbank.org/server/api/item/relateditemlistconfigs/8cdfa3b6-8275-5492-82a2-be3e15d75a49_metadata/itemlist'.
Users also downloaded
Showing related downloaded files
Error: Could not load results for 'https://openknowledge.worldbank.org/server/api/item/relateditemlistconfigs/8cdfa3b6-8275-5492-82a2-be3e15d75a49_downloads/itemlist'.