PUMA Survey 3.1. Insights in societal changes in Austria

DOI

Full edition for scientific use. PUMA Surveys consist of separate modules designed and prepared by different principle investigators. This PUMA Survey consists of three modules. Fieldwork was conducted by Statistics Austria.

MODULE 1 (Ivo Ponocny, Eduard Brandstätter, Christian Weismayer). Self-ratings of life satisfaction and happiness often tend to disclose some harm and mischief people actually experience in life (see Staudinger, 2000, “happiness paradox”, Cummins & Nistico, 2002, “positivity bias”, and Ponocny, Weismayer, Dressler, & Stross, 2017). Therefore, an alternative classification called “narrated well-being” (NWB) was developed by the latter authors which seems to more directly reflect the negative circumstances in people’s lives, as tested on the basis of 500 quality-of-life interviews. However, this rating scheme could only be applied to external ratings of life narratives, but not to self-ratings, a gap to be filled by the present report. Similarly, the assessment of the most influential well- and ill-being drivers via open-ended questions – leaving it to the citizens which aspects of life they want to tell about – was not assessed in a large-scale assessment framework with a representative sampling frame. Furthermore, the question why in part drastic negative circumstance do not produce more negative self-ratings drew the attention on the role of obligation and burden, with the suspicion that persons with obligations tend to emphasize how well they cope with their challenges rather than evaluate based on their personal happiness. If this is true, then there is an ambiguity regarding the meaning of those self-ratings, with the potential for misinterpretation by researchers. These thoughts, if correct, will particularly apply to persons with responsibility for persons dependent on them, such as children and teenagers, and persons giving informal care. Consequently, the research goals are to i) determine the extent of burdensome circumstances, including demanding obligations, in the life of the Austrians ii) and assess in particular to which extent burden and obligations change the meaning of life satisfaction ratings iii) describe the well-being of the Austrian population in terms of the NWB classification, shedding an alternative light on negative life circumstances and their well-being consequences iv) compare the NWB conclusions to the outcome of standard methodology, and evaluate the added value of applying NWB in a large-scale setting, and of including them in official national well-being assessment

MODULE 2 (Hyunjin Song, Homero Gil de Zúñiga, Hajo G. Boomgaarden). This survey module investigates whether and how “News finds me” (NFM) perception is related to diversity and expertise levels of one’s informal political discussion network, and further prompts possible correlates and political consequences of NFM perception. Prior research suggest that social networking sites and digital media become an ever more dominant source through which citizens are exposed to and acquire political information. As citizens rely on social media to provide them with political news, and increasingly “encounter” news and political information inadvertently online, some perceive themselves being well informed about politics without actively seeking political information actively, which we may label as “news finds me” (NFM) perception. This survey module aims to further conceptualize and develop measures of NFM perception, clarifying its internal factor structure, providing evidence of their validity, and further explore possible political correlates of NFM perception. By doing so, this study makes several important contributions. First, this survey module proposes a novel and arguably important construct (NFM perception) that can explain citizen’s political online news consumption behaviors in an era of digital and social media. Second, by developing and accessing the measurement scales reflecting this concept, this study provides evidence for the validity of these measures. Third, it examines how NFM predict affinities for different political system attitudes and support of individuals such as political interest, efficacy, support for democracy, and political cynicisms.

MODULE 3 (Thomas M. Meyer, Markus Wagner). Elections are meant to ensure the formation of governments that represent citizen preferences. Yet, in multi-party democracies election results alone are often not decisive, as no single party wins the majority of votes (or seats). Instead, government formation is the result of (post-election) bargaining processes between potential coalition parties. The question is then whether this government formation process reflects citizen preferences and is seen as legitimate by them. Who do citizens see as legitimate members of coalition governments? In a survey experiment, we show respondents a figure with election results and ask them to evaluate the legitimacy of the two largest parties to direct the government formation process. Using a factorial vignettes design, we expect that the legitimacy of a party’s government mandate depends on 1) change in the electoral support from the previous to the current election, and 2) the type of party system. Specifically, the largest party should be a more legitimate formateur party when 1) it gained rather than lost votes (compared to the previous election) and 2) in party systems where the largest party can form significantly more majority coalitions than any other party.

Probability

Self-administered questionnaire: Paper; Self-administered questionnaire: Web-based

Identifier
DOI https://doi.org/10.11587/QEM0JC
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=5132f687375243bfb9217de915a52eaf0c92004d84c608b4572c4cc01182598f
Provenance
Creator PUMA
Publisher AUSSDA; The Austrian Social Science Data Archive
Publication Year 2018
Rights For more Information please visit AUSSDA's web page
OpenAccess true
Representation
Resource Type Numeric
Discipline Social Sciences
Spatial Coverage Austria