The response of youth to racial discrimination: implications for resilience theory

This paper presents a qualitative participatory study of Canadian young people who identified themselves as visible minorities and who have experienced discrimination based on their skin colour or ethnicity. Eighteen participants aged 15–24 (12 girls and 6 boys), representing four ethnic minority groups, participated in focus groups and in-depth interviews and shared their responses to racial discrimination against them. Analysis of the data from the four discussion groups reveals that racism occurs in everyday situations and places, a lot of times manifesting itself as subtle forms of discrimination. Our findings also suggest that most of the participants tend to employ non-confrontational approaches when dealing with racial violence against them, and provide us with the rationale behind their intentions. Further, youth are not uniformly impacted by racialized events, and therefore the coping strategies they use vary based on individual and contextual factors. Three common strategies for healing can be derived from the participants’ narratives: expressive-emotional, spiritual-forgiving and communicative-relational. We discuss our findings in the light of theoretical frameworks of resilience and coping approaches and argue that young people’s subjective appraisals of racialized events as well as contextual factors need to be addressed in any discussion on coping and resilience within minority youth populations.     

Optimal sampling for spatial prediction of functional data

This paper combines optimal spatial sampling designs with geostatistical analysis of functional data. We propose a methodology and design criteria to find the set of spatial locations that minimizes the variance of the spatial functional prediction at unsampled sites for three functional predictors: ordinary kriging, simple kriging and simple cokriging. The last one is a modification of an existing predictor that uses ordinary cokriging based on the basis coefficients. Instead, we propose to use a simple cokriging predictor with the scores resulting from a representation of the functional data with the empirical functional principal components, allowing to remove restrictions and complexity of the covariance models and constraints on the estimation procedure. The methodology is applied to a network of air quality in Bogotá city, Colombia.