In this programme, we map and examine local labour market programmes (LLMPs) at the municipal level in Sweden. This includes their institutional structure and organisation, as well as the experiences of participants in the programmes, using a longitudinal approach with the aim to improve LLMPs. The long-term goal is to increasing the inclusion of LLMP participants in working life. To answer the programme’s questions, data will be collected and analysed within the four work packages. In each work package, a mixed-method approach is applied with a combination of quantitative and qualitative methods. The programme is informed by three overarching general theoretical approached, tying together institutional ethnography, intersectional studies of structural inequalities on different levels, and the role of emotions in everyday work. At the organisational level (WP 1), we will investigate the circumstances under which LLMPs are performed and negotiated by those involved. Here, the internal organisation, activities and methods are the focus. This approach will result in knowledge about the characteristics of these organisations and the factors promoting the inclusion of underrepresented groups in working life. By examining the activities in LLMPs (WP 2), we will be able to determine how their institutional structure differs between regions in Sweden, how the different municipalities work with labour market policy, how they translate national policy into the local context, how they organise their work and which initiatives they choose to adopt. By examining the individual experiences of those who are directly affected by such incentives (WP 3), knowledge and understanding will be obtained of the connections between experiences and labour market policies. This will give important insights into the functioning of local programmes and of the opportunities to create entry into the labour market. Furthermore, in WP4 we will develop and test an effect evaluation of work methods used in LLMPs and their effect on clients’ progress over time.