Women's rates of remand, or pre-trial detention, have grown dramatically in Australia and the rates at which Aboriginal and Torres Strait Islander women are incarcerated without conviction are particularly high. However, there is little research examining bail and remand practices and their relationship to social inequalities. This article presents findings from research on the drivers behind women's increasing rates of custodial remand in Victoria—a jurisdiction that has significantly restricted access to bail through legislative reforms. Drawing on data derived from interviews with criminal defence and duty lawyers, we outline how bail and remand practices systematically disadvantage women experiencing housing insecurity and domestic and family violence (DFV), increasing their risk of becoming trapped in longer-term cycles of incarceration. Our analysis reinforces the need to move away from 'tough on crime' approaches to bail. It also highlights unintended consequences of DFV reforms, including further marginalising and punishing criminalised women who are victim-survivors.
This article discusses findings from an ethnographic study of a bail and remand court in Victoria, Australia. Through a focus on the sensory dimensions of forced movements within and through the bail court, the article contributes to the burgeoning sub-field of sensory criminology and develops the concept of 'carceral churn'. The article argues that the bail court's churn reproduces criminal and carceral subjects and is implicated in a project of carceral buildup. The churn of the bail court involves forms of mobility and exchange via the inter- and intra-carceral spaces that variously dull, distort, deprive or assault the senses with oppressive effects. This includes both 'new' and 'old' penal technologies such as holding cells, the custody dock, AV links and court-prison transport. The analysis of sensory violence challenges the notion that court 'efficiency' can improve justice experiences and outcomes and instead calls for increased attention to the harms and lethality that flow from carceral churn left un-checked.
AbstractIntroductionHIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small‐area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five‐year age groups.MethodsSmall‐area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district‐level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016–2018.ResultsAdult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty‐eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city.ConclusionsThe Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.
