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Breaking the cycle: Systematic review of perinatal interventions for parents at risk of child removal
Get PDFThis systematic review examined the effectiveness of perinatal interventions aimed at preventing infant removals, with attention to service features, implementation barriers, and enablers. We searched six electronic databases and 15 relevant websites for peer reviewed studies published between 2014 and 2024. Eligible studies evaluated interventions targeting pregnant parents at risk of having another child removed and reported on infant removal outcomes. Independent reviewers screened studies using Covidence. A total of 256 records were obtained, of which six peer reviewed studies covering eight interventions, involving 3,254 pregnant women and 20 professionals met the inclusion criteria. Three studies included comparison groups, including only one randomized controlled trial. Five studies assessed program-level interventions, and one study evaluated a policy change. Risk of bias was assessed using the Mixed Methods Appraisal Tool (MMAT). Two of the three comparative studies indicated that targeted interventions may help reduce infant removals. Four of the six studies highlighted that trauma-informed, relationship-based, and multidisciplinary approaches delivered during pregnancy were associated with reductions in infant removals and improvements in maternal wellbeing, housing stability, substance use, and service engagement. Facilitators of successful implementation included continuity of care, culturally safe and non-judgmental support, and flexible services tailored to family needs. Common barriers were late referrals, limited intervention timelines, mistrust of services particularly among families with prior removals and insecure funding that constrained scale and sustainability. Despite generally positive outcomes, the evidence base remains weak due to small samples, limited diversity, lack of comparison groups, and short follow-up periods. This first systematic review of perinatal interventions for preventing infant removals highlights the need for long term, inclusive, comparative research. It underscores the importance of embedding early, holistic support in routine services and offers valuable insights for policy and practice on supporting parents with complex needs within the child protection system
Trajectory Prediction and Intelligent RSU Handover for Connected Vehicles Using Deep Sequential and Ensemble Learning
No full textAccurate trajectory prediction and proactive Road-Side Unit (RSU)handover are essential for maintaining seamless connectivity and low-latency Multi-Edge Computing (MEC) based services in Cooperative Adaptive Cruise Control (CACC) systems. Conventionally, mobility forecasting and migration decisions are treated as separate problems, neglecting their inherent dependence, thus leading
to premature or delayed handovers. In this work an integrated learning-based pipeline is introduced that first predicts the vehicle mobility using deep sequential models and the leverages these
predictions to trigger intelligent RSU migrations. We employ a LSTM network to learn temporal dynamics from the large-scale FHWA dataset and generate multi-step displacement predictions
over short horizons. These predictions are then used to infer future coverage boundaries and connectivity risks. Further, we model RSU migration as a binary-class classification task and train Random Forest (RF) and Multilayer Perceptron (MLP) as classifiers on engineered mobility features, such as velocities deltas, cumulative drift and distance to RSU markers. To handle skewed migration labels, we incorporate fallback heuristics and class-balanced strategies. Experiments on the 500,000 real vehicular samples reveal that the
RF-based migration model achieves up to 73% accuracy. Meanwhile LSTM maintains stable short-horizon displacement accuracy with competitive Average Displacement Error (ADE) and Final Displacement Error (FDE) scores. Together, the models enable anticipatory RSU handover decisions that outperform naive threshold-based methods
I know I’m not going to have to heal from this”: Women university workers' collective writing on "office housework" as a space for building collective care, healing and hope.
Get PDFHow can we, as women university workers, assert collective writing as a form of resistance to embody our collective and individual struggles and convert them into words? We are a collective of five professional service and three academic women workers who came together to answer this question through writing about our performance of office housework and the gendered invisibility we experienced. We share our collective writing practices as a methodology to create connections and healing between workers divided along neoliberal and patriarchal university structures. Our work offers feminist epistemic resistance through the intentional joining of women university workers as co-producers of knowledge, following the tradition of feminist consciousness-raising groups. Our analysis problematizes the individualization of office housework. It illustrates how saying “no” individualistically is often elusive, because doing so displaces the work onto colleagues with less structural power; nor enough if we are to advance the goal of collectively reimagining how this crucial, yet invisible work can be redistributed more equally amongst all workers. Our collective writing affirms the need for office housework to be recognized and revalued as important and indispensable work that sustains the functioning of our higher education institutions, especially in times of uncertainty and crisis
Think Happy Be Happy: Salesperson’s Personal Happiness and Flourishing
Get PDFAlthough the role of positive emotions is important in sales, personal happiness remains understudied in the selling context. Grounded in broaden-and-build theory, this study aims to examine the relationships among personal happiness, job involvement, job satisfaction and salesperson flourishing. For salespeople, the new demands of a connected world have largely blurred the boundaries between their personal life and work life. It has allowed emotions from their personal life to spill over into their workplace. Data from 137 salespeople in the retail context in India lend support for the proposed serial mediation model. The authors propose that the influence of personal happiness on a salesperson flourishing is mediated by job involvement and job satisfaction. Results of this study shows that personal happiness has a direct influence on the salesperson’s flourishing and is effective only through the mediating influence of job satisfaction and not of job involvement. This study extends the broaden-and-build theory by proposing that personal happiness may influence flourishing at work. The findings illustrate the need for a renewed focus on salesperson’s personal emotions, especially in todays connected workplace where the boundaries between personal and work life are shrinking
Three Models of Aesthetic Recognition
No full textIn this chapter, I argue that the disregard for the aesthetic in the literature on recognition is problematic and shed light on how the aesthetic and recognition interact. I make the original claim that aesthetic recognition denotes a subspecies of recognition. I also show that this model of aesthetic recognition has significant advantages over two alternative models. The first alternative model, proposed by Jacques Rancière, identifies the aesthetic with recognition. However, one drawback of his conceptualization consists in the fact that it cannot underpin a differentiated social critique. The second alternative model, suggested by Jason Miller, maintains that the aesthetic conditions the recognition of cultural identities. I highlight several problems with Miller’s approach. For instance, he fails to fully grasp the differences between Axel Honneth’s and Charles Taylor’s understandings of recognition, and consequently, he does not appreciate Honneth’s reasons for rejecting the idea of cultural recognition. Further, by focusing on cultural identities, he obscures the wider significance of his core insight. I therefore develop a revised version of his model, which maintains that the aesthetic conditions all subspecies of recognition. Finally, I show that this revised model complements my own, according to which aesthetic recognition denotes a subspecies of recognition
Predictive Quantile Regressions with Persistent and Heteroskedastic Predictors: A Powerful 2SLS Testing Approach
Get PDFWe develop new tests for predictability, based on the Lagrange Multiplier [LM] principle, in the context of quantile regression [QR] models which allow for persistent and endogenous predictors driven by conditionally and/or unconditionally heteroskedastic errors. Of the extant predictive QR tests in the literature, only the moving blocks bootstrap implementation, due to Fan and Lee (2019), of theWald-type test of Lee (2016) can allow for conditionally heteroskedastic errors in the context of a QR model with persistent predictors. In common with all other tests in the literature it cannot, however, allow for any form of unconditionally heteroskedastic behaviour in the errors. The LM-based approach we adopt in this paper is obtained from a simple auxiliary linear test regression which facilitates inference based on established instrumental variable methods. We demonstrate that, as a result, the tests we develop, based on either conventional or heteroskedasticity-consistent standard errors in the auxiliary regression, are robust under the null hypothesis of no predictability to conditional heteroskedasticity and to unconditional heteroskedasticity in the errors driving the predictors, with no need for bootstrap implementation. Tests are developed both for predictability at a single quantile, and also jointly over a set of quantiles. Simulation results highlight the superior finite sample size and power properties of our proposed LM tests over the tests of Lee (2016) and Fan and Lee (2019) for both conditionally and unconditionally heteroskedastic errors. An empirical application to the equity premium for the S&P 500 highlights the practical usefulness of our proposed tests, uncovering significant evidence of predictability in the left and right tails of the returns distribution for a number of predictors containing information on market or firm risk
Global value chains, trade facilitation, and the use of environmental management practices in SMEs
Get PDFPurpose: This study investigates the relationship between small and medium enterprises (SMEs) participation in global value chains (GVCs) and the use of environmental management practices. The study examines the role of national governments in shaping this relationship, specifically exploring the role of trade facilitation. The emphasis lies on understanding the extent to which GVCs and governmental policy interaction relate to improved environmental management practices among SMEs.
Design/methodology/approach: The study builds on several publicly available data sources, including the World Bank’s Archival Enterprise Surveys and the OECD Trade Facilitation Indicator. The sample includes 1,462 SMEs in 18 countries. To test our hypotheses, we use regression analysis employing bootstrapping techniques for rigorous testing of direct and indirect associations.
Findings: Results indicate that SMEs tend to use environmental management practices when entering GVCs, but not after exiting. Moreover, the study suggests that a non-linear feature of trade facilitation plays an important role in mitigating the relationship between SMEs exit from GVCs and SMEs abandonment of environmental management practices.
Originality: The relationship between SMEs entering and exiting GVCs and environmental management practices is not well understood. It is still unclear whether the external pressures and governmental policies to stimulate trade contribute to improving the sustainability behaviour of SMEs. This study adds to the operations management literature by relating government policies with the use of environmental management practices, providing insights on the relationship between deglobalisation and SMEs sustainability activities
Household Portfolios and Monetary Policy
Get PDFWe show that expansionary monetary policy is positively (negatively) associated with household portfolio allocation to high-risk (low-risk) assets, in line with ‘reaching for yield’ behaviour. Our main findings are based on an analysis of US household-level data using alternative measures of monetary policy shifts over the period 1999–2007. Using the two-part Fractional Response Model, we show that changes in the Federal Funds Rate (FFR) have a stronger impact on the decision to hold high-risk assets relative to the impact on the decision to hold low-risk assets. In addition, our findings indicate that the impact of FFR changes is stronger for active investors. Finally, our findings are robust over an extended time period (1999–2019) that includes the global financial crisis using a monetary policy measure that accounts for the post-crisis ZLB period
Association of CREB1 (rs2253206) and BDNF (rs6265) Polymorphisms with Implementation Intentions Treatment Response in Smoking Reduction.
Get PDFBackground: Previous studies have shown that implementation intentions are moderately effective in reducing smoking among smokers, but the factors determining its effectiveness are unclear. CREB1 (rs2253206) and BDNF (rs6265) polymorphisms have been proposed as the genes involved in addictive behaviors; therefore, we investigated their association with smokers’ responses to implementation intentions psychotherapy. Methods: This clinical trial was conducted on smoking male students at Tehran University and Shahid Beheshti University. The research sample was 78 smoking students who smoked at least seven cigarettes weekly. All of the participants received an implementation intentions intervention session. Their smoking rates were measured before and after the intervention, and all of them were genotyped for CREB1 (rs2253206) and BDNF (rs6265) using PCR-RFLP. The prospective-retrospective memory questionnaire (PRMQ) was used to evaluate the prospective memory (PM). Analysis of covariance (ANCOVA) and simple linear regression were used to analyze the data using SPSS version 26 at a significance level of 0.05. Results: The results showed that implementation intentions affect smoking reduction (t = 4.44, P = 0.001). Data analysis showed no relationship between these two SNPs and treatment response. Also, no association was observed between these SNPs and PM. However, regression analysis showed that PM could predict the response to treatment (R² = 0.10, F = 12.15, P = 0.001). Conclusion: Implementation intentions can be suitable for reducing smoking. Studying the effect of genetic factors on psychotherapy in larger samples could be an effective way to individualize psychological treatments in reducing smoking, including implementation intentions