Scaling up research on family justice using large-scale administrative data: an invitation to the socio-legal community

This article outlines the value of administrative data for family justice research. Although socio-legal scholars have extended their research beyond purely theoretical or doctrinal analyses, studies using large-scale digital datasets remain few in number. As new opportunities arise to link large-scale administrative datasets across health, education, welfare and justice, it is vital that the community of family justice researchers and analysts are supported to deliver research based on entire service or family court populations. In this context, this article provides a definition of administrative data, before outlining the potential of single, linked or blended administrative data sets for family justice research. The remaining sections of the article speak to questions that are pertinent to this particular academic community, including the distinctive contribution of the socio-legal scholar to interdisciplinary teams and the place of data providers in collaborative research. Drawing on the sociological concept of ‘publics’, the final section considers the multiple interest groups whose social licence must be secured, when personal records are used to understand the relationship between law and family life

Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants

Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (&lt;15 %) uncertainties. However, as the constellation of CO2-observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources.</p

Automated detection and monitoring of methane super-emitters using satellite data

A reduction in anthropogenic methane emissions is vital to limit near-term global warming. A small number of so-called super-emitters is responsible for a disproportionally large fraction of total methane emissions. Since late 2017, the TROPOspheric Monitoring Instrument (TROPOMI) has been in orbit, providing daily global coverage of methane mixing ratios at a resolution of up to 7×5.5 km2, enabling the detection of these super-emitters. However, TROPOMI produces millions of observations each day, which together with the complexity of the methane data, makes manual inspection infeasible. We have therefore designed a two-step machine learning approach using a convolutional neural network to detect plume-like structures in the methane data and subsequently apply a support vector classifier to distinguish the emission plumes from retrieval artifacts. The models are trained on pre-2021 data and subsequently applied to all 2021 observations. We detect 2974 plumes in 2021, with a mean estimated source rate of 44 t h−1 and 5–95th percentile range of 8–122 t h−1. These emissions originate from 94 persistent emission clusters and hundreds of transient sources. Based on bottom-up emission inventories, we find that most detected plumes are related to urban areas and/or landfills (35 %), followed by plumes from gas infrastructure (24 %), oil infrastructure (21 %), and coal mines (20 %). For 12 (clusters of) TROPOMI detections, we tip and cue the targeted observations and analysis of high-resolution satellite instruments to identify the exact sources responsible for these plumes. Using high-resolution observations from GHGSat, PRISMA, and Sentinel-2, we detect and analyze both persistent and transient facility-level emissions underlying the TROPOMI detections. We find emissions from landfills and fossil fuel exploitation facilities, and for the latter, we find up to 10 facilities contributing to one TROPOMI detection. Our automated TROPOMI-based monitoring system in combination with high-resolution satellite data allows for the detection, precise identification, and monitoring of these methane super-emitters, which is essential for mitigating their emissions.</p

Using policy codesign to achieve multi-sector alignment in adolescent behavioral health: a study protocol

Background: Policymaking is quickly gaining focus in the field of implementation science as a potential opportunity for aligning cross-sector systems and introducing incentives to promote population health, including substance use disorders (SUD) and their prevention in adolescents. Policymakers are seen as holding the necessary levers for realigning service infrastructure to more rapidly and effectively address adolescent behavioral health across the continuum of need (prevention through crisis care, mental health, and SUD) and in multiple locations (schools, primary care, community settings). The difficulty of aligning policy intent, policy design, and successful policy implementation is a well-known challenge in the broader public policy and public administration literature that also affects local behavioral health policymaking. This study will examine a blended approach of coproduction and codesign (i.e., Policy Codesign), iteratively developed over multiple years to address problems in policy formation that often lead to poor implementation outcomes. The current study evaluates this scalable approach using reproducible measures to grow the knowledge base in this field of study. Methods: This is a single-arm, longitudinal, staggered implementation study to examine the acceptability and short-term impacts of Policy Codesign in resolving critical challenges in behavioral health policy formation. The aims are to (1) examine the acceptability, feasibility, and reach of Policy Codesign within two geographically distinct counties in Washington state, USA; (2) examine the impact of Policy Codesign on multisector policy development within these counties using social network analysis; and (3) assess the perceived replicability of Policy Codesign among leaders and other staff of policy-oriented state behavioral health intermediary organizations across the USA. Discussion: This study will assess the feasibility of a specific approach to collaborative policy development, Policy Codesign, in two diverse regions. Results will inform a subsequent multi-state study measuring the impact and effectiveness of this approach for achieving multi-sector and evidence informed policy development in adolescent SUD prevention and treatment

Evaluating models of care closer to home for children and young people who are ill: executive summary

Providing care for children who are ill, as close to home as possible, is an objective of health care providers and policy makers nationally and internationally. The existing evidence base to support development of care closer to home (CCTH) is weak in relation to clinical effectiveness, approaches and models, potential costs and benefits to families and the health service, impact on those who use CCTH, and how CCTH is best delivered and organised. This project took a mixed methods approach to address these questions, including a systematic review, a national survey of services and case studies

Evaluating models of care closer to home for children and young people who are ill

Standard six of the National Service Framework (NSF) for Children, Young People and Maternity Services recommends that care for ill children should be delivered as close to home as possible. This research aimed to find evidence about delivering care closer to home (CCTH) for ill children, particularly in relation to: the range and extent of provision, the implications of CCTH for those who plan, deliver, and use such services, and cost effectiveness