Do Youth Employment Programs Improve Labor Market Outcomes? A Systematic Review

This study reviews the evidence on the labor market impact of youth employment programs. We analyze the effectiveness of interventions, and factors that influence program performance including country context, target beneficiaries, program design, implementation, and evaluation type. We identify 113 impact evaluations covering a wide range of methodologies, interventions, and countries. The meta-analysis synthesizes the evidence based on 2,259 effect sizes (Standardized Mean Differences) and the statistical significance of 3,105 impact estimates (Positive and Statistically Significant). Just more than one-third of youth employment program evaluations worldwide show a significant positive impact on labor market outcomes - either employment rates or earnings. In general, programs have been more successful in middle- and low-income countries; this may be because programs' investments are especially helpful for the most vulnerable population groups that they target. We conjecture that recent programs might have benefited from innovations in design and implementation. In middle-low income countries, skills training and entrepreneurship programs have had a higher impact. In high-income countries, the role of intervention type is less decisive - much depends on context and how services are chosen and delivered, a result that holds across country types. We find evidence that programs integrating multiple interventions more likely succeed because they respond better to different needs of beneficiaries. Results also point to the importance of profiling and follow-up systems in determining program performance, as well as to incentive systems for services providers

Do Youth Employment Programs Improve Labor Market Outcomes? A Systematic Review

This study reviews the evidence on the impact of youth employment programs on labor market outcomes. The analysis looks at the effectiveness of various interventions and the factors that influence program performance including country context, targeted beneficiaries, program design and implementation, and type of evaluation. We identify 113 counterfactual impact evaluations covering a wide range of methodologies, interventions, and countries. Using meta-analysis methods, we synthesize the evidence based on 2,259 effect sizes (Standardized Mean Differences, or SMD) and the statistical significance of 3,105 treatment effect estimates (Positive and Statistically Significant, or PSS). Overall, we find that just more than one-third of evaluation results from youth employment programs implemented worldwide show a significant positive impact on labor market outcomes – either employment rates or earnings. In general, programs have been more successful in middle- and low-income countries; this may be because these programs' investments are especially helpful for the most vulnerable population groups – low-skilled, low-income – that they target. We also conjecture that the more-recent programs might have benefited from innovations in design and implementation. Moreover, in middle and low income countries, skills training and entrepreneurship programs seem to have had a higher impact. This does not imply, however, that those programs should be strictly preferred to others; much depends on the needs of beneficiaries and program design. In high-income countries, the role of intervention type is less decisive – much depends on context and how services are chosen and delivered, a result that holds across country types. We find strong evidence that programs that integrate multiple interventions are more likely to succeed because they are better able to respond to the different needs of beneficiaries. We also find evidence about the importance of profiling and follow-up systems in determining program performance, and some evidence about the importance of incentive systems for services providers

New Paradigms in Monetary Theory and Policy?

On 11-12 May 2011, SUERF and the Belgian Financial Forum, in association with the Brussels Finance Institute and the Centre for European Policy Studies (CEPS) organized the 29th SUERF Colloquium “New Paradigms in Money and Finance?” All the papers in the present SUERF Study are based on contributions to the Brussels Colloquium

iAnn: an event sharing platform for the life sciences

Summary: We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available. Availability: http://iann.pro/iannviewer Contact: [email protected]

Entropy based blending of policies for multi-agent coexistence

Research on multi-agent interaction involving humans is still in its infancy. Most approaches have focused on environments with collaborative human behavior or a small, defined set of situations. When deploying robots in human-inhabited environments in the future, the diversity of interactions surpasses the capabilities of pre-trained collaboration models. ”Coexistence” environments, characterized by agents with varying or partially aligned objectives, present a unique challenge for robotic collaboration. Traditional reinforcement learning methods fall short in these settings. These approaches lack the flexibility to adapt to changing agent counts or task requirements without undergoing retraining. Moreover, existing models do not adequately support scenarios where robots should exhibit helpful behavior toward others without compromising their primary goals. To tackle this issue, we introduce a novel framework that decomposes interaction and task-solving into separate learning problems and blends the resulting policies at inference time using a goal inference model for task estimation. We create impact-aware agents and linearly scale the cost of training agents with the number of agents and available tasks. To this end, a weighting function blending action distributions for individual interactions with the original task action distribution is proposed. To support our claims we demonstrate that our framework scales in task and agent count across several environments and considers collaboration opportunities when present. The new learning paradigm opens the path to more complex multi-robot, multi-human interactions

Reduced antimicrobial consumption through enhanced pneumonia management in critically ill patients: outcomes of an antibiotic stewardship program in the intensive care unit

BackgroundCritically ill patients in the intensive care unit (ICU) who are suspected of having pneumonia are frequently treated with broad-spectrum antimicrobials even when the diagnosis remains uncertain. While appropriate antimicrobial therapy offers undeniable benefits, its inappropriate or excessive use can lead to harmful side effects. This study examines the impact of an antimicrobial stewardship program (ASP) in the ICU on both diagnostic accuracy and antimicrobial consumption in critically ill patients with pneumonia.MethodsThis cohort study compares a prospective cohort with matched controls from a retrospective sample in the ICU of a tertiary hospital. An ASP was implemented focusing on microbiological sampling of bacteria and antimicrobial therapy. Primary endpoint was days of therapy (DOTs). Secondary endpoints were number of respiratory samples (RS), identification of relevant bacteria in RS and diagnostic accuracy of pneumonia. Clinical safety outcome parameters were length of stay, length of invasive mechanical ventilation and ICU mortality until day 28.ResultsA total of 200 patients were assigned to the intervention group (IG) and 200 to the control group (CG). The overall DOTs per patient were 12.95 [95% confidence interval (CI) 11.42 to 14.47] in the CG compared to 9.91 (CI 8.97 to 10.82) in the IG (p = 0.036), with no unfavorable findings in safety outcome parameters. DOTs for meropenem were 2.74 (CI 2.14 to 3.34) in the CG vs. 1.13 (CI 0.76 to 1.49) in the IG (p < 0.001), DOTs for piperacillin/tazobactam were 3.66 (CI 3.16 to 4.15) vs. 2.78 (CI 2.33 to 3.22; p = 0.011), and DOTs for ampicillin/sulbactam were 1.49 (CI 1.15 to 1.82) vs. 2.63 (CI 2.25 to 3.02; p < 0.001). Relevant bacteria in RS were detected more frequently in the IG, with n = 91 compared to n = 61 in the CG (p = 0.003).ConclusionImplementation of an ASP in the ICU effectively reduces broad-spectrum antimicrobial consumption in critically ill patients with pneumonia without compromising patient safety

‘Q-storming’ to identify challenges and opportunities for integrating health and climate adaptation measures in Africa

INTRODUCTION : Climate factors influence the state of human health and wellbeing. Climate-related threats are particularly being experienced by vulnerable populations in Africa. A Question (Q)-Storming session was convened at an international climate adaptation conference. It promoted dialog among a diverse spectrum of researchers, climate and medical scientists, health professionals, national government officials, civil society, business, and international governing organizations. The session identified approaches for the effective integration of health within African national climate adaptation policies. MATERIALS AND METHODS : Two organizations partnered to convene the session at the Adaptations Futures 2018 Conference in Cape Town. Q-storming (which is an inverse approach to brainstorming) was applied to extract ideas from all participants. Four topics were presented during the session: (i) adaptive capacities related to climate change and infectious diseases; (ii) adaptive capacity of African governments in relation to health and climate change; (iii) making climate science work to protect the health of vulnerable populations; and (iv) making climate-health research usable. RESULTS : Nine cross-cutting adaptation themes were generated (i.e. key definitions, adaptive capacity, health sector priorities, resources, operational capacities and procedures, contextual conditions, information pathways, and information utility). The Q-Storming approach was a valuable tool for improving the understanding of the complexities of climate-health research collaborations, and priority identification for improved adaptation and service delivery. CONCLUSION : Concerted recognition regarding difficulties in linking climate science and health vulnerability at the interface of practitioners and decision-makers is required, for better integration and use of climate-health research in climate adaptation in Africa. This can be achieved by innovations offered through Q-Storming.The World Health Organization, Clim-Health Africa, Natural Environment Research Council, the South African government via the South African Medical Research Council and an Oppenheimer Memorial Trust International Fellowship.http://www.elsevier.com/joclimam2024Geography, Geoinformatics and MeteorologySDG-03:Good heatlh and well-beingSDG-13:Climate actio