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Causal attributions are an element of a frame (Entman, 1991). Furthermore, a causal attribution organizes the anatomy of a problem within a text. Hereby, causal attributions provide explanations of problems in terms of their expectations, the underlying reasons or the causes that led to one or more problems depicted in the text. Entry connected to framing devices cultural motifs Field of Application/Theoretical Foundation The causal attributions variable is used in both deductive and inductive framework analyses (e.g., Boesman Cools et al., 2024; Van Gorp, 2007, 2010). Frame analyses with a socio-constructionist approach (Van Gorp, 2007) discuss a strong correlation of causal attributions with cultural motifs (Gamson Pentzold Van Gorp (2) definition of the problem; (3) cause (why is it a problem?); (4) consequences; (5) moral values involved; (6) possible solutions/actions; (7) metaphors, choice of vocabulary. Values: The qualitative analysis resulted in a total of twelve frame packages (six frames and six counter-frames). Each consists of a central cultural theme, a definition of dementia, the causes and possible consequences, the moral evaluation and possible future scenarios of dementia. (1A. Dualism of body and mind vs. 1B. Unity of body and mind; 2; The invader; 3. The strange travelling companion; 4A. Faith in science vs. 4B. Natural ageing; 5. The fear of death and degeneration; 6. Carpe diem; 7A. Reversed roles vs. 7B. Each in turn; 8A. No quid pro quo vs. 8B. The Good Mother) Reliability: First, both authors coded independently of each other and met to discuss differences. This resulted in tentative frames which were used for further qualitative research of the material. Then, the frames found were discussed with experts (in a workshop setting). Codebook: Description of the sample (newspapers and audiovisual material) can be found at the end of the article (appendix of Van Gorp Entman, 1991, p. 52). These four elements are the reasoning devices of a frame. They are accompanied by the so-called framing devices which are stylistic devices, catchphrases, metaphors, and references. To that end, for the manual frame analysis on Big Data in the press aggregates, we developed codes for framing devices (1), reasoning devices (2), and cultural motifs (3). All three elements form part of a frame package (Van Gorp, 2007, 2010). To build the frame packages, we followed procedures of both block modeling and cluster analysis. First, a block modeling was conducted – as introduced by White for structural analyses (White et al., 1976) – to prepare the data set for the cluster analysis. Then, the coded cultural motifs, the reasoning devices, and the framing devices that correlated strongly in the data set (a total of 9 variables and 34 codes) were chosen. With that, a hierarchical cluster analysis (Ward method) was conducted (Matthes but only one per propositional unit) Values: see Table 1. Reliability: α = .669 Krippendorff’s alpha, intercoder reliability. A total of seven reliability tests were conducted, five of them during the coding phase and two as part of two pretests. Five coders were involved in four tests, four coders were involved in three tests. All tests were conducted in the period July 2022 to December 2022. Table 1 Values used for the variable causal attributions described for Big Data (Pentzold Big Data is used to predict future health and to cure / heal diseases; also research purposes for scientific purposes (to find something out) 2 military/governmental exploitation new technologies (AI, drones and robots) collect data and/or can be used for surveillance and defense, for military intelligence, police investigations, data for security: push-pull between privacy and security in the digital age 3 data as resource to make profit / sell data, also meta data; Advances in workflows: detailed information about consumers/workers/employees: data profiles (consumers, economic dimension), profiling social behavior and mobility patterns, consumer behavior, social media marketing, analyzing meta data to predict the future of what people will buy (not) buy, predicting consumer trends, changes on the labor market, economic developments, the machines that store data and the technologies that collect it are becoming increasingly efficient. this can save costs. 4 detailed information about voters; behavioural microtargeting (political dimension) voter mobilization; predicting voting behavior 5 networked architectures (macro) databases are globally connected, the technical infrastructures are already established, lower costs for data collection and storage, people are proceeded into data; free Services from companies for the price of some data, monitoring as default citizens get used to 6 risks of datafication are abstract, not considered (macro) lack of citizen interest and privacy interests in Big Data, “trends and changes are neglected” 7 deficient laws politically not regulated, in-transparency of contracts, police investigations are not regulated, grappling with balance of power: who will make decisions for us in the future? Ubiquitous mass surveillance; lack of expertise in handling Big Data (lack of organization of accumulated Big Data), persistence of data as data shadows (in the most negative sense: identities can be stolen) 8 Terror attacks in the past Big data analyses to prevent terrorist attacks like 9/11 9 something else/ nothing detected Note: No multiple coding. References Boesman, J., & Van Gorp, B. (2018). Driving The Frame: How News Values, News Pegs, and Story Angles Guide Journalistic Frame Building. In P. D’Angelo (Ed.), Communication Series. Doing news framing analysis II: Empirical and theoretical perspectives (Second edition, pp. 112–134). New York: Routledge Taylor & Francis Group. Cools, H., Van Gorp, B., & Opgenhaffen, M. (2024). Where exactly between utopia and dystopia? A framing analysis of AI and automation in US newspapers. Journalism, 25(1), 3–21. https://doi.org/10.1177/14648849221122647 Entman, R. M. (1991). Framing U.S. Coverage of International News: Contrasts in Narratives of the KAL and Iran Air Incidents: Symposium. Journal of Communication, 41(4), 6–27. Gamson, W. A., & Modigliani, A. (1989). Media Discourse and Public Opinion on Nuclear Power: A Constructionist Approach. American Journal of Sociology, 95(1), 1–37. https://www.jstor.org/stable/2780405 Jasanoff, S. (2015). Future Imperfect. In S. Jasanoff & S. Kim (Eds.), Dreamscapes of Modernity (pp. 1–33). Chicago: University of Chicago Press. Matthes, J., & Kohring, M. (2008). The Content Analysis of Media Frames: Toward Improving Reliability and Validity. Journal of Communication, 58(2), 258–279. https://doi.org/10.1111/j.1460-2466.2008.00384.x Pentzold, C., & Fischer, C. (2017). Framing Big Data: The discursive construction of a radio cell query in Germany. Big Data & Society, July-December, 1–11. https://doi.org/10.1177/2053951717745897 Pentzold, C. & Knorr, C. (2024). Making Sense of “Big Data”: Ten Years of Discourse Around Datafication (ICA 2024, 74th Conference, Gold Coast, Australia). Pentzold, C., & Knorr, C. (2021-2024). Framing Big Data (DFG). Leipzig University. https://www.sozphil.uni-leipzig.de/en/institut-fuer-kommunikations-und-medienwissenschaft/professuren/chair-of-media-and-communication/forschungs-und-praxisprojekte/framing-big-data van Atteveldt, W. (2008). Semantic network analysis: Techniques for extracting, representing and querying media content. SIKS dissertation series: no. 2008-30. BookSurge. Van Gorp, B. (2007). The Constructionist Approach to Framing: Bringing Culture Back In. Communication Research, 57, 60–78. Van Gorp, B. (2010). Strategies to Take Subjectivity Out of Framing Analysis. In P. D´Angelo & J. A. Kuypers (Eds.), Communication Series. Doing News Framing Analysis: Empirical and Theoretical Perspectives (pp. 84–109). New York: Routledge. Van Gorp, B., & Vercruysse, T. (2012). Frames and counter-frames giving meaning to dementia: A framing analysis of media content. Social Science & Medicine (1982), 74(8), 1274–1281. https://doi.org/10.1016/j.socscimed.2011.12.045 White, H. C., Boorman, S. A., & Breiger, R. L. (1976). Social Structure from Multiple Networks. I. Blockmodels of Roles and Positions. American Journal of Sociology, 81(4), 730–780. http://www.jstor.org/stable/2777596
Knorr et al. (Thu,) studied this question.