Software Training in HEP

The long-term sustainability of the high-energy physics (HEP) research software ecosystem is essential to the field. With new facilities and upgrades coming online throughout the 2020s, this will only become increasingly important. Meeting the sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g., Unix, version control, C++, and continuous integration). The second is knowledge of domain-specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving specialized techniques, including parallel programming, machine learning and data science tools, and techniques to maintain software projects at all scales. This paper discusses the collective software training program in HEP led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients for the solution of HEP computing challenges. Beyond serving the community by ensuring that members are able to pursue research goals, the program serves individuals by providing intellectual capital and transferable skills important to careers in the realm of software and computing, inside or outside HEP

Software Training in HEP

The long-term sustainability of the high-energy physics (HEP) research software ecosystem is essential to the field. With new facilities and upgrades coming online throughout the 2020s, this will only become increasingly important. Meeting the sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g., Unix, version control, C++, and continuous integration). The second is knowledge of domain-specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving specialized techniques, including parallel programming, machine learning and data science tools, and techniques to maintain software projects at all scales. This paper discusses the collective software training program in HEP led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients for the solution of HEP computing challenges. Beyond serving the community by ensuring that members are able to pursue research goals, the program serves individuals by providing intellectual capital and transferable skills important to careers in the realm of software and computing, inside or outside HEP

Materialism and the Boomerang Effect of Descriptive Norm Demarketing: Extension and Remedy in an Environmental Context

Household consumption has a major impact on the ecological environment. Still, research on effective approaches to reduce consumption is in the early stages. For example, it is not clear whether a widely used approach-descriptive norm demarketing-is effective. Some evidence suggests that this approach actually triggers a boomerang effect, enhancing consumption among some consumer groups. With two experiments (online and lab), the current research contributes to prior work on demarketing and social norms in multiple ways. First, whereas prior work has tested the impact of descriptive norm demarketing on consumer groups classified according to their consumption/usage levels, the current work classifies consumers according to the value system that underlies consumption-that is, materialism. Second, whereas evidence on the boomerang effect has mostly appeared in the energy domain, this research demonstrates the effect across numerous consumption contexts. Third, this research offers a potential remedy to the boomerang effect-namely, carbon labeling that emphasizes the ecological damage of consumption. Finally, the key outcome tested empirically is the actual ecological consequences of consumer behavior in terms of carbon footprint