Christoph Kern
Biographic Data
| ID | 384607 |
|---|---|
| NAME | Christoph Kern |
| GIVEN NAMES | Christoph |
| FAMILY NAME | Kern |
| SIGNATURE | KERN C |
| AFFILIATIONS | University of Mannheim |
| ORCID | 0000-0001-7363-4299 |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 15 |
| AUTHOR COUNT | 19 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2004 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
Prediction-Based Adaptive Designs for Reducing Wave Nonresponse Rates and Bias in Panel Surveys
Machine learning (ML)-based nonresponse prediction in panel surveys enables selective interventions. However, the optimal use of ML predictions in Adaptive Survey Design (ASD) remains uncertain. We propose a method that integrates field experiment results on incentives, questionnaire length, and questionnaire content with ML-based propensity models to simulate ASD strategies ex-post with minimal assumptions. Using German panel data, we show that …
Measuring public opinion towards artificial intelligence
The rapid proliferation of artificial intelligence (AI) has sparked both enthusiasm and ethical concerns in societies. As AI continues to permeate daily life, policymakers need to understand how it is perceived by diverse stakeholders and communities. To reliably measure attitudes towards AI of the general public, a short scale is essential for universal application. Existing scales face limitations in applicability due to their length, sub-stand…
Transparency, neutrality, voice, and respect
Public attitudes toward artificial intelligence (AI) are often explained in terms of users’ perceived costs and benefits. More recent research emphasizes societal concerns and procedural fairness, yet these different dimensions have rarely been integrated into a unified explanatory framework. This article offers the first joint domain-general test of outcome- and process-oriented approaches to explain public acceptability of AI. We argue that bel…
The sound of respondents
Web surveys completed on smartphones open novel ways for measuring respondents’ attitudes, behaviors, and beliefs that are crucial for social science research and many adjacent research fields. In this study, we make use of the built-in microphones of smartphones to record voice answers in a smartphone survey and extract non-verbal cues, such as amplitudes and pitches, from the collected voice data. This allows us to predict respondents’ level of…
Latent Variable Forests for Latent Variable Score Estimation
We develop a latent variable forest (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on confirmatory factor analysis (CFA) models with ordinal and/or numerical response variables. Through parametric model restrictions paired with a nonparametric tree-based machine learning approach, LV Forest estimates latent variable scores using models…
Bridging the gap
AI-driven decision-making systems are becoming instrumental in the public sector, with applications spanning areas like criminal justice, social welfare, financial fraud detection, and public health. While these systems offer great potential benefits to institutional decision-making processes, such as improved efficiency and reliability, these systems face the challenge of aligning machine learning (ML) models with the complex realities of public…
The multimodal Munich Clinical Deep Phenotyping study to bridge the translational gap in severe mental illness treatment research
The identification of cross-diagnostic and diagnosis-specific biotype-informed subgroups of patients and the translational dissection of those subgroups may help to pave the way toward precision medicine with artificial intelligence-supported tailored interventions and treatment. This aim is particularly important in psychiatry, a field where innovation is urgently needed because specific symptom domains, such as negative symptoms and cognitive d…
From fair predictions to just decisions? Conceptualizing algorithmic fairness and distributive justice in the context of data-driven decision-making
Prediction algorithms are regularly used to support and automate high-stakes policy decisions about the allocation of scarce public resources. However, data-driven decision-making raises problems of algorithmic fairness and justice. So far, fairness and justice are frequently conflated, with the consequence that distributive justice concerns are not addressed explicitly. In this paper, we approach this issue by distinguishing (a) fairness as a pr…
A preregistered vignette experiment on determinants of health data sharing behavior
The COVID-19 pandemic has spotlighted the importance of high-quality data for empirical health research and evidence-based political decision-making. To leverage the full potential of these data, a better understanding of the determinants and conditions under which people are willing to share their health data is critical. Building on the privacy theory of contextual integrity, the privacy calculus, and previous findings regarding different data …
Social impacts of algorithmic decision-making
Academic and public debates are increasingly concerned with the question whether and how algorithmic decision-making (ADM) may reinforce social inequality. Most previous research on this topic originates from computer science. The social sciences, however, have huge potentials to contribute to research on social consequences of ADM. Based on a process model of ADM systems, we demonstrate how social sciences may advance the literature on the impac…
Global trends and predictors of face mask usage during the Covid-19 pandemic
The decision to wear a face mask in public settings is significantly associated with sociodemographic factors, risky social behaviors, and mask policies. This has important implications for health prevention policies and messaging, including the potential need for more targeted policy and messaging design
Completion Conditions and Response Behavior in Smartphone Surveys
This study utilizes acceleration data from smartphone sensors to predict motion conditions of smartphone respondents. Specifically, we predict whether respondents are moving or nonmoving on a survey page level to learn about distractions and the situational conditions under which respondents complete smartphone surveys. The predicted motion conditions allow us to (1) estimate the proportion of smartphone respondents who are moving during survey c…
Predicting Voting Behavior Using Digital Trace Data
A major concern arising from ubiquitous tracking of individuals’ online activity is that algorithms may be trained to predict personal sensitive information, even for users who do not wish to reveal such information. Although previous research has shown that digital trace data can accurately predict sociodemographic characteristics, little is known about the potentials of such data to predict sensitive outcomes. Against this background, we invest…
Modelling Decision-Making Processes of Regional Mobility in a Dyadic Framework
Analysing mobility decisions has been on the research agenda of various disciplines for many years, resulting in a diversity of conceptual and statistical approaches. However, previous empirical studies typically model regional mobility from an actor-centred perspective which lacks to take the contextual embeddedness of individuals in regions and partnerships into account. Against this background, this study proposes a multilevel dyadic approach …
Dyadische Analyse regionaler Arbeitsmarktmobilität
Dyadische Analyse regionaler Arbeits -marktmobilität
Jürgen Friedrichs / Alexandra Nonnenmacher (Hrsg.), Soziale Kontexte und soziale Mechanismen. Sonderheft 54 der Kölner Zeitschrift für Soziologie und Sozialpsychologie. Wiesbaden
Article Jürgen Friedrichs / Alexandra Nonnenmacher (Hrsg.), Soziale Kontexte und soziale Mechanismen. Sonderheft 54 der Kölner Zeitschrift für Soziologie und Sozialpsychologie. Wiesbaden: Springer VS 2014, 438 S., kt., 49,99 € was published on July 1, 2016 in the journal Soziologische Revue (volume 39, issue 3).
Das neue Europäische Erbstatut und seine Aufnahme in der deutschen Literatur
The New European Conflicts Rule on Succession and its Reception by German Legal Literature On 16 August 2012, Regulation (EU) No. 650/2012 on jurisdiction, applicable law, recognition and enforcement of decisions and acceptance and enforcement of authentic instruments in matters of succession and on the creation of a European Certificate of Succession was finally adopted. The Regulation's basic conflicts rule is that, in the absence of a choice o…
Die Sicherheit gedeckter Wertpapiere
Entscheidend für die Sicherheit von Wertpapieren, bei denen bestimmte 'Deckungswerte' oder 'assets' die Erfüllung der verbrieften Zahlungsansprüche gewährleisten sollen, ist zum einen, durch welche juristische Konstruktion die den Anlegern haftende 'Deckungsmasse' gebildet wird, zum anderen, ob diese Deckung zur Befriedigung der Anleger tatsächlich ausreicht. Im kontinentaleuropäischen und im anglo-amerikanischen Rechtsraum begegnet man vielfälti…
Predicting Voting Behavior Using Digital Trace Data
A major concern arising from ubiquitous tracking of individuals’ online activity is that algorithms may be trained to predict personal sensitive information, even for users who do not wish to reveal such information. Although previous research has shown that digital trace data can accurately predict sociodemographic characteristics, little is known about the potentials of such data to predict sensitive outcomes. Against this background, we invest…
A preregistered vignette experiment on determinants of health data sharing behavior
The COVID-19 pandemic has spotlighted the importance of high-quality data for empirical health research and evidence-based political decision-making. To leverage the full potential of these data, a better understanding of the determinants and conditions under which people are willing to share their health data is critical. Building on the privacy theory of contextual integrity, the privacy calculus, and previous findings regarding different data …
Social impacts of algorithmic decision-making
Academic and public debates are increasingly concerned with the question whether and how algorithmic decision-making (ADM) may reinforce social inequality. Most previous research on this topic originates from computer science. The social sciences, however, have huge potentials to contribute to research on social consequences of ADM. Based on a process model of ADM systems, we demonstrate how social sciences may advance the literature on the impac…
Modelling Decision-Making Processes of Regional Mobility in a Dyadic Framework
Analysing mobility decisions has been on the research agenda of various disciplines for many years, resulting in a diversity of conceptual and statistical approaches. However, previous empirical studies typically model regional mobility from an actor-centred perspective which lacks to take the contextual embeddedness of individuals in regions and partnerships into account. Against this background, this study proposes a multilevel dyadic approach …
Die Sicherheit gedeckter Wertpapiere
Entscheidend für die Sicherheit von Wertpapieren, bei denen bestimmte 'Deckungswerte' oder 'assets' die Erfüllung der verbrieften Zahlungsansprüche gewährleisten sollen, ist zum einen, durch welche juristische Konstruktion die den Anlegern haftende 'Deckungsmasse' gebildet wird, zum anderen, ob diese Deckung zur Befriedigung der Anleger tatsächlich ausreicht. Im kontinentaleuropäischen und im anglo-amerikanischen Rechtsraum begegnet man vielfälti…
Das neue Europäische Erbstatut und seine Aufnahme in der deutschen Literatur
The New European Conflicts Rule on Succession and its Reception by German Legal Literature On 16 August 2012, Regulation (EU) No. 650/2012 on jurisdiction, applicable law, recognition and enforcement of decisions and acceptance and enforcement of authentic instruments in matters of succession and on the creation of a European Certificate of Succession was finally adopted. The Regulation's basic conflicts rule is that, in the absence of a choice o…
Jürgen Friedrichs / Alexandra Nonnenmacher (Hrsg.), Soziale Kontexte und soziale Mechanismen. Sonderheft 54 der Kölner Zeitschrift für Soziologie und Sozialpsychologie. Wiesbaden
Article Jürgen Friedrichs / Alexandra Nonnenmacher (Hrsg.), Soziale Kontexte und soziale Mechanismen. Sonderheft 54 der Kölner Zeitschrift für Soziologie und Sozialpsychologie. Wiesbaden: Springer VS 2014, 438 S., kt., 49,99 € was published on July 1, 2016 in the journal Soziologische Revue (volume 39, issue 3).
Dyadische Analyse regionaler Arbeitsmarktmobilität
Dyadische Analyse regionaler Arbeits -marktmobilität
Modelling Decision-Making Processes of Regional Mobility in a Dyadic Framework
Analysing mobility decisions has been on the research agenda of various disciplines for many years, resulting in a diversity of conceptual and statistical approaches. However, previous empirical studies typically model regional mobility from an actor-centred perspective which lacks to take the contextual embeddedness of individuals in regions and partnerships into account. Against this background, this study proposes a multilevel dyadic approach …
Predicting Voting Behavior Using Digital Trace Data
A major concern arising from ubiquitous tracking of individuals’ online activity is that algorithms may be trained to predict personal sensitive information, even for users who do not wish to reveal such information. Although previous research has shown that digital trace data can accurately predict sociodemographic characteristics, little is known about the potentials of such data to predict sensitive outcomes. Against this background, we invest…
Completion Conditions and Response Behavior in Smartphone Surveys
This study utilizes acceleration data from smartphone sensors to predict motion conditions of smartphone respondents. Specifically, we predict whether respondents are moving or nonmoving on a survey page level to learn about distractions and the situational conditions under which respondents complete smartphone surveys. The predicted motion conditions allow us to (1) estimate the proportion of smartphone respondents who are moving during survey c…
Global trends and predictors of face mask usage during the Covid-19 pandemic
The decision to wear a face mask in public settings is significantly associated with sociodemographic factors, risky social behaviors, and mask policies. This has important implications for health prevention policies and messaging, including the potential need for more targeted policy and messaging design
From fair predictions to just decisions? Conceptualizing algorithmic fairness and distributive justice in the context of data-driven decision-making
Prediction algorithms are regularly used to support and automate high-stakes policy decisions about the allocation of scarce public resources. However, data-driven decision-making raises problems of algorithmic fairness and justice. So far, fairness and justice are frequently conflated, with the consequence that distributive justice concerns are not addressed explicitly. In this paper, we approach this issue by distinguishing (a) fairness as a pr…
A preregistered vignette experiment on determinants of health data sharing behavior
The COVID-19 pandemic has spotlighted the importance of high-quality data for empirical health research and evidence-based political decision-making. To leverage the full potential of these data, a better understanding of the determinants and conditions under which people are willing to share their health data is critical. Building on the privacy theory of contextual integrity, the privacy calculus, and previous findings regarding different data …
Social impacts of algorithmic decision-making
Academic and public debates are increasingly concerned with the question whether and how algorithmic decision-making (ADM) may reinforce social inequality. Most previous research on this topic originates from computer science. The social sciences, however, have huge potentials to contribute to research on social consequences of ADM. Based on a process model of ADM systems, we demonstrate how social sciences may advance the literature on the impac…
The multimodal Munich Clinical Deep Phenotyping study to bridge the translational gap in severe mental illness treatment research
The identification of cross-diagnostic and diagnosis-specific biotype-informed subgroups of patients and the translational dissection of those subgroups may help to pave the way toward precision medicine with artificial intelligence-supported tailored interventions and treatment. This aim is particularly important in psychiatry, a field where innovation is urgently needed because specific symptom domains, such as negative symptoms and cognitive d…
The sound of respondents
Web surveys completed on smartphones open novel ways for measuring respondents’ attitudes, behaviors, and beliefs that are crucial for social science research and many adjacent research fields. In this study, we make use of the built-in microphones of smartphones to record voice answers in a smartphone survey and extract non-verbal cues, such as amplitudes and pitches, from the collected voice data. This allows us to predict respondents’ level of…
Latent Variable Forests for Latent Variable Score Estimation
We develop a latent variable forest (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on confirmatory factor analysis (CFA) models with ordinal and/or numerical response variables. Through parametric model restrictions paired with a nonparametric tree-based machine learning approach, LV Forest estimates latent variable scores using models…
Bridging the gap
AI-driven decision-making systems are becoming instrumental in the public sector, with applications spanning areas like criminal justice, social welfare, financial fraud detection, and public health. While these systems offer great potential benefits to institutional decision-making processes, such as improved efficiency and reliability, these systems face the challenge of aligning machine learning (ML) models with the complex realities of public…
Prediction-Based Adaptive Designs for Reducing Wave Nonresponse Rates and Bias in Panel Surveys
Machine learning (ML)-based nonresponse prediction in panel surveys enables selective interventions. However, the optimal use of ML predictions in Adaptive Survey Design (ASD) remains uncertain. We propose a method that integrates field experiment results on incentives, questionnaire length, and questionnaire content with ML-based propensity models to simulate ASD strategies ex-post with minimal assumptions. Using German panel data, we show that …
Measuring public opinion towards artificial intelligence
The rapid proliferation of artificial intelligence (AI) has sparked both enthusiasm and ethical concerns in societies. As AI continues to permeate daily life, policymakers need to understand how it is perceived by diverse stakeholders and communities. To reliably measure attitudes towards AI of the general public, a short scale is essential for universal application. Existing scales face limitations in applicability due to their length, sub-stand…
Transparency, neutrality, voice, and respect
Public attitudes toward artificial intelligence (AI) are often explained in terms of users’ perceived costs and benefits. More recent research emphasizes societal concerns and procedural fairness, yet these different dimensions have rarely been integrated into a unified explanatory framework. This article offers the first joint domain-general test of outcome- and process-oriented approaches to explain public acceptability of AI. We argue that bel…
Computer Science (9 works) · Psychology (8 works) · Political science (6 works) · Geography (5 works) · Mathematics (5 works) · Sociology (5 works) · Ethics and Social Impacts of AI (4 works) · Medicine (3 works) · Social Psychology (3 works) · Statistics (3 works)