Useless Apprentice: An Intervention Study of the Danish Construction Industry

Abstract

This thesis aims at answering the following problem statement: How can the construction industry in Denmark create a more inclusive work environment, where diversity is valued, and employee well-being is increased? How is it possible for an individual to thrive at work when it risks a lack of recognition or social exclusion? In the previous years, more and more organizations have become aware of workplace violation, bullying, sexual harassment and discrimination. The construction industry in Denmark has long aimed at increasing the general proportion of women, which has not changed in the past 20 years. Moreover, with the rise of foreign workers, the majority of this industry, being predominately white, middleaged, cis-gendered males, must find a way to work with inclusion to enhance the overall well-being of all employees. The research strategy for this study is to conduct our take on action research in the form of InclusionLAB. InclusionLAB is thus the primary method for data collection, where recent and relevant studies serve as secondary data. This mix of methods gives us the ability to explore the Danish construction industry from a point of sensemaking where the experiences of apprentices as well, as other employees within the industry, are explored. The findings of this study reveal an industry that experiences low tolerance for individuals that do not fit the cultural norms as well as a strong feeling of pride in the professional work. This low tolerance often manifests itself in humor, jokes and discrimination. Therefore, employees with minority status identities tend to downplay these to ‘fit in’ i.e., seek belongingness. As individuals experience a lack of psychological safety, the industry finds itself unable to challenge norms which result in less inclusion. We argue that InclusionLAB can be applied as a practical initiative to make employees aware of the norms in the industry, hence creating awareness of implicit and explicit bias, while also creating tangible solutions for organizations to implement.