The material in this article is extracted from an empirical study of industrial and agricultural businesses' responses to regulation of health and safety in the workplace. The study critically assesses the philosophy of self‐regulation which underpins the regulatory framework in England and within the context of the expectations of employers built into that philosophy, attempts to distinguish between different models of employers in relation to their levels of motivation toward health and safety issues; their knowledge and comprehension of the law; their general approach to compliance with regulations; and their response to inspectors' enforcement activities. The article concludes that self‐regulation is only capable of operating under very narrow conditions. It is at its most successful within the largest and most hazardous companies, despite the fact that the inspectorates devote the greatest concentration of enforcement and advisory resources to these sites. Companies which do not have a natural interest in safety require considerable advice, encouragement and coercion. In some situations deterrent penalties may be required in order to achieve a sustained improvement in standards. The research suggests that greater attention should be paid to the variety of employers and their compliance strategies, and to the potential for better targeting of regulatory efforts.

Justiciable problems do not always occur in isolation. However, little empirical research has examined multiple problems in depth by identifying common clusters of problems, their extent, and those who experience them. The Legal Services Research Centre's Periodic Survey of Justiciable Problems is a large-scale survey undertaken in England and Wales, documenting 5,611 respondents' experience of 21 discrete problem categories. Having assessed the overall incidence and overlap of problem types, hierarchical cluster analysis, based on each respondent's experience of these categories, was used to identify clusters. We then established social and demographic predictors of each cluster using mixed-effects Poisson regression and examined each problem type's likelihood of overlapping with further problems, both within and between identified clusters. We highlight policy implications of our findings, particularly concerning developing "joined-up" solutions to multiple "joined-up" problems.