Selected Publications

We examine how descriptive representation, formal representation, and responsiveness affect the legitimacy of political decisions: Who are the representatives, how are they selected, what is the outcome of the decision-making process, and to what extent do these three aspects matter for decision acceptance among the citizens? We examine this from the citizens’ perspective, and ask whether decisions are perceived as more legitimate when they are made by groups that reflect society in certain characteristics and chosen according to certain selection procedures. In a Norwegian survey experiment, we find that people are more willing to accept a decision when it is made by a group of people like them, and who are assigned as decision makers based on their expertise. Descriptive representation also serves as a cushion for unfavorable decisions. Moreover, when asked, the traditionally less advantaged groups tend to value descriptive representation more than other citizens.
In Comparative Political Studies,2017
Preprint Project

Opinion polls may inadvertently affect public opinion, as people may change their attitudes after learning what others think. A disconcerting possibility is that opinion polls have the ability to create information cascades, wherein the majority opinion becomes increasingly larger over time. Testing poll influence on attitudes toward Syrian refugees and mandatory measles vaccination, we field survey experiments on a probability-based online survey panel. Through a novel automated procedure labeled the dynamic response feedback, we measure whether the answers from early poll respondents can influence the opinions of subsequent respondents who learn the answers of the previous respondents. Using this procedure, no feedback loops are identified.
In Social Science Computer Review,2017
Preprint

Democracies are typically considered more legitimate than other types of regimes because they allow the citizens to participate in the policy decision-making process. Others argue that the policy output matters most, and citizen influence plays a lesser role. This study presents two survey experiments on the micro foundations of these two sources of political legitimacy, thus contributing to an emerging literature that experimentally investigates the effects of democratic procedures in small-scale settings. Respondents who saw the decision going in their favour found the decision much more acceptable than the respondents who preferred another outcome. Conversely, decision-making influence generally did not serve as a legitimising factor among the respondents. This result supports the argument that citizens prefer a stealth democracy where they are minimally involved in democratic decision-making processes.
In Political Studies,2017
Preprint Project

Projects

Public Fairness Perceptions of Algorithmic Governance

This proposal aims to study what fairness perceptions citizens adhere to in relation to governance decisions based on algorithmic information processing, and how its use may affect democratic legitimacy. Such procedures are increasingly being introduced by government institutions to help making decisions that impact individual citizens on topics such as giving defendants parole, approving immigration applications, and determining eligibility for welfare programs. Thus, we are on the verge of a revolution in public sector decision-making processes, where computers will take over many of the governance tasks previously assigned to human bureaucrats. With it, the conditions for impartial and transparent treatment of citizens are changing. Increased capacity to process relevant information enhances the potential for making more accurate and efficient judgments. Yet, we also run the risk of creating a black box society where citizens are being kept in the dark about the decision-making processes that affect their lives, potentially undermining the legitimacy of governmental institutions among the citizens they serve. While significant attention in the recent few years has been devoted to normative discussions on fairness, accountability, and transparency related to algorithmic decision making, little is still known about citizens’ views on this issue. There is thus an imminent need to study these emerging governance developments from a political science perspective. This proposal aims to fill this gap by organizing both in-depth group discussions on this topic among representative samples of the Norwegian population through deliberative polling, as well as conduct survey experiments on larger representative survey samples. The Center for Deliberative Democracy at Stanford University and The Digital Social Science Core Facilities (DIGSSCORE) at the University of Bergen are involved in the project, ensuring high data quality from top social science infrastructures.

Demokratiske algoritmer: Hvordan oppnå legitimitet og rettferdighet i automatiserte beslutningsprosesser i offentlig forvaltning

Den pågående automatiseringen av beslutningsprosesser i offentlig forvaltning representerer en omveltning innenfor byråkratisk myndighetsutøvelse. Tilgang på store mengder relevant digital data og økende muligheter for å behandle informasjonen gjør at oppgaver som tidligere måtte behandles manuelt kan overlates til hel- eller halvautomatiserte prosesser med vesentlig redusert menneskelig inngripen. På den ene siden gir denne utviklingen store effektiviseringsmuligheter og potensial for offentlige besparelser. På den andre siden er ivaretakelsen av forvaltningens legitimitet i befolkningen et risikoaspekt i denne utviklingen. Det overordnede målet med det foreslåtte prosjektet er å kartlegge ut fra et demokratiperspektiv om, og i så fall hvordan, oppfattelsen av NAV som institusjon blant innbyggere i Norge påvirkes av en overgang til økt grad av automatisert saksbehandling. For å besvare forskningsspørsmålene vil vi våren 2021 gjennomføre en spørreundersøkelse i Norsk medborgerpanel, som er et befolkningsrepresentativt panel som samler inn data til forskningsformål.

The European Prediction Market Infrastructure for Political Events - EPIPE

The European Prediction Market Infrastructure for Political Elections develops and facilitates the use of prediction market software for research purposes in relation to elections and other political events. The software has been employed to Norwegian national elections, German national elections, Spanish national and regional government formations, and to Swiss national elections and popular votes.

Procedural Legitimacy

The primary scientific objective of the PROLEG project is to better understand how democratic institutions and decision-making bodies should organize decision-making procedures and implementation procedures in order to make them more legitimate in the eyes of the public. We study if and how variations in political decision making procedures can make the outcomes more acceptable to the citizens, and especially to those who disagree with the outcome. Do people share universal perceptions of fair decision makingn procedures? In a nutshell, the PROLEG project will address this issue and generate new knowledge that can be used to improve governance in the future. This will be accomplished by conducting experimental and observational studies on the mechanisms of accepting decision-making procedures. The data will mainly be generated within the infrastructure of DIGSSCORE at the University of Bergen, Norway, taking advantage of changes in technology and research methodology that combine to bring computer laboratory research and survey studies closer together.

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