Month: August 2024

Empowerment and Substance Use Prevention among Youth of Color: A Scoping Review

Latest Results

Abstract

Purpose of the Review

Concerns related to harmful substance use during adolescence continue to persist, and recent trends show racial and ethnic disparities. There is a need to identify effective and culturally responsive prevention approaches focused on communities of color. Innovative approaches to substance use prevention and youth health equity have included those based on youth empowerment and community-based participatory research. The purposes of this review were to incorporate studies that describe youth of color engagement and empowerment in substance use prevention, with a primary emphasis on alcohol use, and to identify related outcome studies.

Recent Findings

This scoping review synthesized studies into empowerment-based youth participatory action research and empowerment theory outcome-based studies. Findings describe participant descriptions, objectives, participatory approaches, primary substances of foci, and youth empowerment-based outcomes.

Summary

Implications provide guidelines for youth empowerment within substance use prevention programming and recommendations for youth-engaged substance use prevention research. Additional research is needed within the area of alcohol use prevention, specifically.

Assessing livelihood vulnerability of rural communities in the wake of recurrent tropical flood hazards in India

Latest Results

Abstract

Tropical riverine floods have escalated their frequency and magnitude causing individual and community-level livelihood vulnerability, especially in the rural areas. Livelihood vulnerability induces social vulnerability in a community in the face of recurrent floods. Thus, while measuring livelihood vulnerability, the non-technocratic factors were emphasized. The livelihood vulnerability index (LVI) devised by the Intergovernmental Panel on Climate Change in 2007 is a widely accepted livelihood vulnerability framework that is applied in the present study to reveal the nature of exposure, sensitivity, and adaptive capacity of rural communities. The study measures 36 parameters based mainly on the primary field survey of 2382 households in the Mayurakshi River Basin (India) along with district census reports, annual flood reports, satellite images and topographical maps. The result depicts that Kandi is the most exposed community development block (score: 0.591) owing to low-lying topography and drainage congestion, with a greater adaptive capacity (score: 0.480) on account of the receipt of higher foreign remittances. Thus, floods could not escalate the livelihood vulnerability due to the rural communities’ higher adaptive capacity. However, the nature of the LVI is primarily determined by the flood hazards, as shown by the close clustering of LVI and exposure using principal component analysis. The hierarchical cluster analysis depicts that the northern part of the study area, characterized by the lower flood hazards, is distinctly separated from the southern part in terms of the LVI. The one-way ANOVA also found significant differences (p < 0.05) among the villages based on exposure and LVI. These findings help various stakeholders to prepare flood management plans.

Assessing livelihood vulnerability of rural communities in the wake of recurrent tropical flood hazards in India

Latest Results

Abstract

Tropical riverine floods have escalated their frequency and magnitude causing individual and community-level livelihood vulnerability, especially in the rural areas. Livelihood vulnerability induces social vulnerability in a community in the face of recurrent floods. Thus, while measuring livelihood vulnerability, the non-technocratic factors were emphasized. The livelihood vulnerability index (LVI) devised by the Intergovernmental Panel on Climate Change in 2007 is a widely accepted livelihood vulnerability framework that is applied in the present study to reveal the nature of exposure, sensitivity, and adaptive capacity of rural communities. The study measures 36 parameters based mainly on the primary field survey of 2382 households in the Mayurakshi River Basin (India) along with district census reports, annual flood reports, satellite images and topographical maps. The result depicts that Kandi is the most exposed community development block (score: 0.591) owing to low-lying topography and drainage congestion, with a greater adaptive capacity (score: 0.480) on account of the receipt of higher foreign remittances. Thus, floods could not escalate the livelihood vulnerability due to the rural communities’ higher adaptive capacity. However, the nature of the LVI is primarily determined by the flood hazards, as shown by the close clustering of LVI and exposure using principal component analysis. The hierarchical cluster analysis depicts that the northern part of the study area, characterized by the lower flood hazards, is distinctly separated from the southern part in terms of the LVI. The one-way ANOVA also found significant differences (p < 0.05) among the villages based on exposure and LVI. These findings help various stakeholders to prepare flood management plans.

Evaluation of Multi-Physics Ensemble Prediction of Monsoon Rainfall Over Odisha, the Eastern Coast of India

Latest Results

Abstract

Selecting proper parameterization scheme combinations for a particular application is of great interest to Weather Research and Forecasting (WRF) model users. The goal of this research is to create an objective method for identifying a set of scheme combinations to form a Multi-Physics Ensemble (MPE) suitable for short-term precipitation forecasting over Odisha, India’s east coast state. In this study, five member ensembles for Cloud Microphysics (CMP) and Land Surface Model (LSM, conventional ensemble) are created, as well as an ensemble of the top five performing members (optimized ensemble) for 13 Monsoon Depressions (MD) and 8 Deep Depression (DD) cases. There are a total of 30 combinations (5 PBL * 5 CMP, 5 LSM with best PBL and CMP, and one with ISRO Land Use Land Cover data). WRF 4.1 is used to carry out simulations, which are initialized with ERA5 reanalysis data and have a 72-h lead time. Rainfall verification skill scores indicate that ensemble members perform significantly better than any deterministic model. Rainfall characteristics such as location, intensity, and time of occurrence are well predicted in ensemble members as measured by a higher correlation coefficient and a lower RMSE. Neighbourhood ensemble probability also demonstrates that ensemble members have a higher chance of detecting heavy to very heavy rainfall events with more spatial accuracy. The study also concludes that choice of parameterization also affects large-scale dynamical parameters (temperature, humidity, wind, hydrometeors) and thus associated rainfall. Ensemble members exhibited less bias in the composite analysis of large-scale parameters. Furthermore, a composite analysis of moisture budget components revealed that the convergence term is the most important component of moisture accumulation, resulting in rainfall during the monsoon low-pressure system. These findings indicate that the proposed method is an effective method for reducing bias in rainfall forecasts.

Evaluation of Multi-Physics Ensemble Prediction of Monsoon Rainfall Over Odisha, the Eastern Coast of India

Latest Results

Abstract

Selecting proper parameterization scheme combinations for a particular application is of great interest to Weather Research and Forecasting (WRF) model users. The goal of this research is to create an objective method for identifying a set of scheme combinations to form a Multi-Physics Ensemble (MPE) suitable for short-term precipitation forecasting over Odisha, India’s east coast state. In this study, five member ensembles for Cloud Microphysics (CMP) and Land Surface Model (LSM, conventional ensemble) are created, as well as an ensemble of the top five performing members (optimized ensemble) for 13 Monsoon Depressions (MD) and 8 Deep Depression (DD) cases. There are a total of 30 combinations (5 PBL * 5 CMP, 5 LSM with best PBL and CMP, and one with ISRO Land Use Land Cover data). WRF 4.1 is used to carry out simulations, which are initialized with ERA5 reanalysis data and have a 72-h lead time. Rainfall verification skill scores indicate that ensemble members perform significantly better than any deterministic model. Rainfall characteristics such as location, intensity, and time of occurrence are well predicted in ensemble members as measured by a higher correlation coefficient and a lower RMSE. Neighbourhood ensemble probability also demonstrates that ensemble members have a higher chance of detecting heavy to very heavy rainfall events with more spatial accuracy. The study also concludes that choice of parameterization also affects large-scale dynamical parameters (temperature, humidity, wind, hydrometeors) and thus associated rainfall. Ensemble members exhibited less bias in the composite analysis of large-scale parameters. Furthermore, a composite analysis of moisture budget components revealed that the convergence term is the most important component of moisture accumulation, resulting in rainfall during the monsoon low-pressure system. These findings indicate that the proposed method is an effective method for reducing bias in rainfall forecasts.

Nine months of daily LiDAR, orthophotos and MetOcean data from the eroding soft cliff coast at Happisburgh, UK

Latest Results

Abstract

The dynamic interaction between cliff, beach and shore-platform is key to assessing the sediment balance for coastal erosion risk assessments, but this is poorly understood. We present a dataset containing daily, 3D,colour LiDAR scans of a 450 m coastal section at Happisburgh, Norfolk, UK. This previously para-glaciated region comprises mixed sand-gravel sediments, which are less well-understood and well-studied than sandy beaches. From Apr-Dec 2019, 236 daily surveys were carried out. The dataset presented includes: survey areas, transects LiDAR scans, georeferenced orthophotos, meteorological- and oceanographical conditions during the Apr-Dec observation period. Full LiDAR point-clouds are available for 67 scans (Oct-Dec). Hourly time-series of offshore sea-state parameters (significant wave height, mean propagation direction, selected spectral periods) were obtained by downscaling the ERA5 global reanalysis data (global atmosphere, land surface and ocean waves) using the numerical model Simulating Waves Nearshore (SWAN). We indicate how to obtain hourly precipitation time-series by interpolating ERA5 data. This dataset is important for researchers understanding the interaction between cliff, beach and shore-platform in open-coast mixed-sand-gravel environments.

Markets and Public Goods: Integrity, Trust, and Climate Change

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Abstract

Public goods are an anomaly in neoclassical economics, a form of ‘market failure’. They exist outside the efficient and equitable optimality of market exchange. It can be shown however that competitive markets are only efficient in short product cycles. Long-term objectives require social support. Corruption arises from the consequent private public interaction. Integrity, the absence of corruption, is a public good. Corruption has risen since the 1980s with privatization and outsourcing. How did European governments become honest in the first place? In the century after the 1770s, they moved from regarding public office as a form of private property to a conception of serving the public good. This integrity revolution was facilitated by Weberian bureaucracies, selected by academic merit and committed to impartiality by long-term incentives. The neoliberal revolution of the 1980s regarded bureaucracies as obstructive and slow. It admired the business corporation with its opaque procedures and charismatic leadership. Concurrently economics moved from neoclassical harmony theory to an asymmetric information model of ‘opportunism with guile’, providing doctrinal legitimacy for corruption. Corporate advertising is deliberately deceptive, and undermines the public good of trustworthiness. Digital platforms, powered by advertising, have subverted public discourse. Misinformation and disinformation have become prime risk factors for current societies. The practical operation of markets undermines the public goods of integrity and trustworthiness. The public good of a habitable climate cannot be achieved by market methods. For long-term payoffs, ‘free markets’ are a harmful delusion, inefficient, corrupt, impossible to achieve, and not sustainable.

A commentary on transformative consumer research: Musings on its genesis, evolution, and opportunity for scientific specialization

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Abstract

Transformative Consumer Research (TCR) was launched in 2005 with the intention to improve and maintain well-being as it is affected by the immense growth and array of worldwide consumption activities. In many respects, through the efforts of a multitude of people, TCR has flourished. But businesses, societies, technologies, and ecologies are also evolving, and TCR has related gaps of thinking and doing. To continue its evolution, and to ultimately realize its potential to become a successful ‘scientific specialty,’ TCR needs to undertake more ground-breaking goals and projects if it is to achieve its valiant mission. In this commentary, we sketch TCR’s development and assess its disciplinarity and opportunities through literature on the science of science. From those insights, we offer a range of options and activities that TCR adherents should consider in order to foster new, courageous, and valuable ventures.

A commentary on transformative consumer research: Musings on its genesis, evolution, and opportunity for scientific specialization

Latest Results

Abstract

Transformative Consumer Research (TCR) was launched in 2005 with the intention to improve and maintain well-being as it is affected by the immense growth and array of worldwide consumption activities. In many respects, through the efforts of a multitude of people, TCR has flourished. But businesses, societies, technologies, and ecologies are also evolving, and TCR has related gaps of thinking and doing. To continue its evolution, and to ultimately realize its potential to become a successful ‘scientific specialty,’ TCR needs to undertake more ground-breaking goals and projects if it is to achieve its valiant mission. In this commentary, we sketch TCR’s development and assess its disciplinarity and opportunities through literature on the science of science. From those insights, we offer a range of options and activities that TCR adherents should consider in order to foster new, courageous, and valuable ventures.