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The aim of this paper is to describe the use of sequence analysis to model trajectories of life‐course economic activity status, within a broader research agenda aimed at improving understanding of the relationship between socioeconomic position and health.

The analysis used data on 288 participants of the Boyd Orr Stratified Sub‐Sample, comprising a combination of prospective and retrospective information on economic activity status, as well as health in early old age. Economic activity was coded as a time‐based sequence of states for each participant based on six‐month periods throughout their lives. Economic activity was classified as: pre‐labour market; full‐time employment; part‐time employment; housewife; made redundant; stopped work due to illness; retired; other unemployed; or not applicable. Optimal matching analysis was carried out to produce a matrix of distances between each sequence, which was then used as the basis for cluster analysis.

The optimal matching analysis resulted in the classification of individuals into five economic activity status trajectories: full‐time workers (transitional exit), part‐time housewives, career breakers, full‐time workers (late entry, early exit), and full‐time housewives.

The paper presents the case for using sequence analysis as a methodological tool to facilitate a more interdisciplinary approach to the measurement of the life‐course socioeconomic position, in particular attempting to integrate the empirical emphasis of epidemiological research with the more theoretical contributions of sociology. This may in turn help generate a framework within which to examine the relationships between life‐course socioeconomic position and outcomes such as health in later life.

The aim of the present study is to identify the prevalent model of social enterprise governance in South Korea by empirically testing five conceptual models. Theoretical and empirical research on the governance of social enterprises have grown considerably in the past decade, centred primarily on the UK, Europe and the USA. Whilst some articles have discussed the role and growth of social enterprises in Asia, the empirical evidence remains scant, particularly in relation to empirical studies of social enterprise governance in South Korea.

Drawing upon established literature on social enterprise governance, we empirically tested five conceptual models on a sample of 69 South Korean social enterprises collected through an online survey to identify the prevalent model of governance. Such models were found unable to fully explain governance processes observed. Thus, the authors used an innovative statistical technique, latent class analysis, which identifies clusters of associations between key governance variables.

This exercise revealed two opposite models, centralising and interdependent. The latter represent an interesting shift towards widening forms of participation in governance processes in South Korea.

The sample is small and only limited to some social enterprise types. More research needs to be done on larger samples including the growing South Korean co-operative sector.

To the authors’ knowledge, this is the first published data available on the governance of South Korean social enterprises and the analysis used to identify governance models (i.e. latent class analysis) is novel.