Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E S ABSTRACTImpacts of Informal Caregiving on Caregiver Employment, Health, and Family *As the aging population increases, the demand for informal caregiving is becoming an ever more important concern for researchers and policy-makers alike. To shed light on the implications of informal caregiving, this paper reviews current research on its impact on three areas of caregivers' lives: employment, health, and family. Because the literature is inherently interdisciplinary, the research designs, sampling procedures, and statistical methods used are heterogeneous. Nevertheless, we are still able to draw several conclusions: first, despite the prevalence of informal caregiving and its primary association with lower levels of employment, the affected labor force is seemingly small. Second, such caregiving tends to lower the quality of the caregiver's psychological health, which also has a negative impact on physical health outcomes. Third, the implications for family life remain under investigated. The research findings also differ strongly among subgroups, although they do suggest that female, spousal, and intense caregivers tend to be the most affected by caregiving.JEL Classification: E26, J14, J46

y * This version of the article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the publisher's final version AKA Version of Record.

Impacts of Informal Caregiving on CaregiverEmployment, Health, and Family *As the aging population increases, the demand for informal caregiving is becoming an ever more important concern for researchers and policy-makers alike. To shed light on the implications of informal caregiving, this paper reviews current research on its impact on three areas of caregivers' lives: employment, health, and family. Because the literature is inherently interdisciplinary, the research designs, sampling procedures, and statistical methods used are heterogeneous. Nevertheless, we are still able to draw several conclusions: first, despite the prevalence of informal caregiving and its primary association with lower levels of employment, the affected labor force is seemingly small. Second, such caregiving tends to lower the quality of the caregiver's psychological health, which also has a negative impact on physical health outcomes. Third, the implications for family life remain under investigated. The research findings also differ strongly among subgroups, although they do suggest that female, spousal, and intense caregivers tend to be the most affected by caregiving.

Human activities are degrading ecosystems worldwide, posing existential threats for biodiversity and humankind. Slowing and reversing this degradation will require profound and widespread changes to human behaviour. Behavioural scientists are therefore well placed to contribute intellectual leadership in this area. This Perspective aims to stimulate a marked increase in the amount and breadth of behavioural research addressing this challenge. First, we describe the importance of the biodiversity crisis for human and non-human prosperity and the central role of human behaviour in reversing this decline. Next, we discuss key gaps in our understanding of how to achieve behaviour change for biodiversity conservation and suggest how to identify key behaviour changes and actors capable of improving biodiversity outcomes. Finally, we outline the core components for building a robust evidence base and suggest priority research questions for behavioural scientists to explore in opening a new frontier of behavioural science for the benefit of nature and human wellbeing.

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This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved.

One challenge that social media platforms are facing nowadays is hate speech. Hence, automatic hate speech detection has been increasingly researched in recent years -in particular with the rise of deep learning. A problem of these models is their vulnerability to undesirable bias in training data. We investigate the impact of political bias on hate speech classification by constructing three politicallybiased data sets (left-wing, right-wing, politically neutral) and compare the performance of classifiers trained on them. We show that (1) political bias negatively impairs the performance of hate speech classifiers and (2) an explainable machine learning model can help to visualize such bias within the training data. The results show that political bias in training data has an impact on hate speech classification and can become a serious issue.

BackgroundLiterature reports a direct relation between nurses’ job satisfaction and their job retention (stickiness). The proper planning and management of the nursing labor market necessitates the understanding of job satisfaction and retention trends. The objectives of the study are to identify trends in, and the interrelation between, the job satisfaction and job stickiness of German nurses in the 1990–2013 period using a flexible specification for job satisfaction that includes different time periods and to also identify the main determinants of nurse job stickiness in Germany and test whether these determinants have changed over the last two decades.MethodsThe development of job stickiness in Germany is depicted by a subset of data from the German Socio-Economic Panel (1990–2013), with each survey respondent assigned a unique identifier used to calculate the year-to-year transition probability of remaining in the current position. The changing association between job satisfaction and job stickiness is measured using job satisfaction data and multivariate regressions assessing whether certain job stickiness determinants have changed over the study period.ResultsBetween 1990 and 2013, the job stickiness of German nurses increased from 83 to 91%, while their job satisfaction underwent a steady and gradual decline, dropping by 7.5%. We attribute this paradoxical result to the changing association between job satisfaction and job stickiness; that is, for a given level of job (dis)satisfaction, nurses show a higher stickiness rate in more recent years than in the past, which might be partially explained by the rise in part-time employment during this period. The main determinants of stickiness, whose importance has not changed in the past two decades, are wages, tenure, personal health, and household structure.ConclusionsThe paradoxical relation between job satisfaction and job stickiness in the German nursing context could be explained by historical downsizing trends in hospitals, an East-West German nurse compensation gap, and an increase in the proportion of nurses employed on a part-time basis. A clearer analysis of each of these trends is thus essential for the development of evidence-based policies that enhance the job satisfaction and efficiency of the German nursing workforce.