It is assumed in Western society that women want to become mothers. This desire is situated within the ideology of the 'perfect mother'. However, feminists have highlighted contradictions between this ideology and the reality of mothering. A trend towards later motherhood has recently been identified. Delayed motherhood has been associated with a number of advantages such as a sense of psychological readiness, however this may mask some of its negative aspects. The aim of the study reported here was to explore the transition to, and lived experience of, delayed motherhood. Five women who were over 30 prior to the birth of their first child were interviewed. A narrative analysis at the personal, interpersonal and societal levels was conducted. At the personal level, diverse stories which contained both problems in adapting to motherhood and also progressive aspects of positive experiences and integration of maternal identities were told. At the interpersonal level, the prominence of the 'double-edged' tone conveyed maternal ambivalence. At the societal level, dominant ideologies of the 'good mother' and normative development were identified. Though the women actively constructed their stories and attempted to resist dominant representations, this analysis emphasises the need for more realistic portrayals of delayed motherhood.

Two National Risk Assessments (NRA) of money laundering (ML) have now been published in the United Kingdom (see HM Treasury 2015 and 2017). While both represent an attempt to identify the risks of ML, there are limitations in relation to the conceptual framework and the methodology used. This paper reviews the UK NRAs and considers whether revision of the methodology employed could help to both remedy these limitations and generate more robust findings. Drawing upon the findings of the UK strand of project Identifying and Assessing the Risk of Money Laundering in Europe (IARM), it outlines how a composite ML risk indicator was developed through analysis of threats and vulnerabilities across 43 police areas. The findings demonstrate that risks are highest in the City of London and the Metropolitan Police area, which is largely explained by the presence of organised crime groups, connections to risky jurisdictions and the cash intensity of businesses. Although the findings should be treated with caution, it is posited that this methodology could be used to help future NRAs develop a more robust framework to understand ML risk and ultimately develop more effective preventative strategies.