37 research outputs found

    Afboeking bijstandsschuld nauwelijks effect op werk en mentale gezondheid

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    Een aanzienlijk deel van de Nederlandse huishoudens heeft te maken met schuldenproblematiek, wat ten koste gaat van hun welzijn. Wat zijn de effecten van een afboeking van bijstandsschulden op werk, het gebruik van bijstand en de mentale gezondheid? Een analyse aan de hand van een natuurlijk experiment in de gemeente Rotterdam

    Architecture and performance of the KM3NeT front-end firmware

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    The KM3NeT infrastructure consists of two deep-sea neutrino telescopes being deployed in the Mediterranean Sea. The telescopes will detect extraterrestrial and atmospheric neutrinos by means of the incident photons induced by the passage of relativistic charged particles through the seawater as a consequence of a neutrino interaction. The telescopes are configured in a three-dimensional grid of digital optical modules, each hosting 31 photomultipliers. The photomultiplier signals produced by the incident Cherenkov photons are converted into digital information consisting of the integrated pulse duration and the time at which it surpasses a chosen threshold. The digitization is done by means of time to digital converters (TDCs) embedded in the field programmable gate array of the central logic board. Subsequently, a state machine formats the acquired data for its transmission to shore. We present the architecture and performance of the front-end firmware consisting of the TDCs and the state machine

    Event reconstruction for KM3NeT/ORCA using convolutional neural networks

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    The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

    Event reconstruction for KM3NeT/ORCA using convolutional neural networks

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    The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

    The financial and administrative burden of financially vulnerable households

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    A substantial part of households in developed countries is financially vulnerable. These households face financial problems or are financially at risk for shocks in income or expenditures. Financially vulnerable households face financial burdens as managing their household finances is complex, requires ongoing attention, and may evoke worries, anxiety, and stress. Beyond financial burdens, financially vulnerable households may also encounter administrative burdens (learning, compliance, and psychological costs) in their interactions with the government. This dissertation aims at gaining insight into sources, consequences, and potential solutions for the financial and administrative burden faced by financially vulnerable households. The results of this dissertation contribute to financial burden research in several respects. We show that difficulties with making ends meet and low income act as primary sources of financial worry and rumination. Additionally, our literature review confirms that financial scarcity creates specific psychological mechanisms and subsequently affects borrowing and consumption decisions. Evidence that financial scarcity affects economic decision making via cognitive load is mixed at best. Furthermore, our findings confirm that behaviorally informed financial education can be effective although its potential in alleviating financial burden seems to be limited. In examining administrative burden, this dissertation has focused on subjective regulatory burden experienced by social benefit claimants. Our findings confirm that both state actions and psychological factors contribute to experiencing subjective regulatory burden. Remarkably, exempting social assistance claimants from labor and reintegration requirements did not significantly reduce their levels of subjective regulatory burden. I discuss the implications of these findings for the psychology of poverty literature and the debate about objective and subjective poverty. Additionally, I propose some potential alternative sources, consequences, and solutions for administrative burden, describe the limitations of this dissertation, and provide directions for future research. The findings presented in this dissertation result in some practical recommendations and considerations for addressing the financial and administrative burden experienced by financially vulnerable households

    A Behaviorally Informed Financial Education Program for the Financially Vulnerable: Design and Effectiveness

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    This dataset contains replication data and codes for the paper "A Behaviorally informed financial education program for the financially vulnerable: Design and effectiveness". In collaboration with five Dutch field partners, we conducted a quasi-experimental field study among financially vulnerable individuals (mostly: clients of municipal debt services). In this study, we tested the effectiveness of a Behaviorally informed financial education program in comparison with both a control group and a traditional program group. We collected data both before the program started and six months later. In comparison with the control group, we found a strong positive effect of the behaviorally informed program on financial skills and knowledge and on financial behavior, but not on financial wellbeing and financial outcomes. Contrary to our expectations, we did not find evidence that the behaviorally informed program performed better than a traditional program. See also dataset "Naar een effectieve budgetcursus" for data and codes used for the research report

    Towards an effective budget course: Naar een effectieve budgetcursus

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    This data set contains data of financially vulnerable individuals who participated in the project ‘Towards an effective budget course’ in 2017 – 2019. In collaboration with five Dutch local government or debt counseling organizations, we conducted a quasi-experimental field experiment. Financially vulnerable individuals are often associated with suboptimal financial behaviors. Evaluated financial education programs so far show difficulties to effectively reach this target population. To solve this problem, we built a behaviorally informed financial education program incorporating insights from motivational and behavioral change theories. In a field experiment among Dutch financially vulnerable people, we compared this program both with a control and a traditional program group. We collected data both before the program started and six months later. In comparison with the control group, we found a strong positive effect of the behavioral informed program on financial behavior, mainly explained by improved budgeting scores. Additionally, we found some evidence for a positive effect on financial skills and knowledge, but not on other outcomes. Contrary to our expectations, we did not detect any evidence that the behaviorally informed program performed better than a traditional program

    Determinants of financial worry and rumination

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    Significant parts of populations in developed countries frequently worry and ruminate about their finances. Financial worry and rumination can have serious psychological consequences, resulting in lower psychological well-being, mental-health problems, and impaired cognitive functioning. The literature lacks studies investigating the socio-demographic antecedents of and the financial processes underlying financial worry and rumination. The purpose of our study was to investigate the socio-demographic and financial antecedents of financial worry and rumination (FWR) and the financial factors mediating these relationships. We collected online self-administered survey data from a sample of the Dutch population (N = 1040). Using confirmatory factor analysis, we found that a bifactor model, including a strong and reliable general factor, provided the best explanation of the structure underlying FWR. We developed a parallel mediation model and investigated its structural relationships using structural equation modeling. After controlling for multiple hypotheses testing, our results show that income, past positive changes in one's finances, and age are negatively related to FWR. We found no support for education level and only weak support for expected changes in one's finances as antecedents. Furthermore, the explained variance in FWR substantially improved after adding the mediators of making ends meet, financial buffer, and perceived debts. Among these mediators, making ends meet played a key role explaining respectively half and two-thirds of the total effects of income and past changes in one's finances on FWR. These results were robust under several specifications and were generalizable to the Dutch population. We discuss the implications of our results for future research and government policy.</p

    Poverty and economic decision making : a review of scarcity theory

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    Poverty is associated with a wide range of counterproductive economic behaviors. Scarcity theory proposes that poverty itself induces a scarcity mindset, which subsequently forces the poor into suboptimal decisions and behaviors. The purpose of our work is to provide an integrated, up-to-date, critical review of this theory. To this end, we reviewed the empirical evidence for three fundamental propositions: (1) Poverty leads to attentional focus and neglect causing overborrowing, (2) poverty induces trade-off thinking resulting in more consistent consumption decisions, and (3) poverty reduces mental bandwidth and subsequently increases time discounting and risk aversion. Our findings indicate that the current literature predominantly confirms the first and second proposition, although methodological issues prevent a firm conclusion. Evidence for the third proposition was not conclusive. Additionally, we evaluated the overall status of scarcity theory. Although the theory provides an original, coherent, and parsimonious explanation for the relationship between financial scarcity and economic decision making, the theory does not fully accord with the data and lacks some precision. We conclude that both theoretical and empirical work are needed to build a stronger theory.</p
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