HOW IS TRUST CHANGING IN INSTITUTIONS?
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Fulvia Pennoni
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This story tells of the evolution of trust analyzed through a statistical model. Statistics provides data analysis tools, it is naturally interdisciplinary, and it allows us to clarify some aspects of collective phenomena
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The characteristics of a society can be more clearly understood through statistical analyses and quantitative modeling of latent traits and their uncertainty, such as trust and perceptions [1]
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This work analyzes the trust of Polish citizens in national institutions and the European Parliament [2] Trust towards institutions is important because it is arguably the foundation of society, of its economy, and of sustainable development [3]
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Using data collected from a sample of the population which is analysed by a statistical model, we can outline the development of a phenomenon and how it applies to the entire population
... and use this to make predictions
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In Poland, due to the economic and financial crisis that started in 2007, citizens' unconditional trust in institutions has declined dramatically [4] Selected people (10,728) were invited to express their opinions over a period starting from 2009…
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... and again in 2011, 2013, and 2015 These years represent a period of great social change in Poland, following the large scale national reform program started in 2011
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Each respondent (defined as “statistical unit”) was asked to answer the same question: “Do you trust in…?”
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and questions asked about the trust placed in 11 public and private institutions, including the Police, banks, insurance companies, the Courts, etc... and in one supranational institution: that of the European Parliament
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The respondent could state: “YES”, “NO”, or “NO OPINION” otherwise he/she could opt not to answer (“MISSING”)
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The analysis of the observed responses for the European Parliament showed that the percentage of indifferent people (“NO OPINION”) decreased significantly from 2009 to 2015 - from 51% to 25% The percentage of those having confidence in the European Parliament (“YES”) has risen from 15% to 38%, while the percentage of those answering “NO” has remained constant at a rather high 33%
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Using a hidden Markov model [5] the responses are used to classify people into groups showing different degrees of trust
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From the results, four categories of people are identified: the disheartened… (or distrustful)
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The indifferent...
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... the selective ones, i.e. those who only trust in certain institutions
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... and the trustful (or confident people), who place their trust in all institutions
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The results show that citizens with specific socio-demographic characteristics are more likely to belong to one category than another The model allows us to detect whether, for example, men or women, or workers or the unemployed are more confident, whether single or married people are more selective, or whether people living in urban or rural areas are more indifferent
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Education is a key feature in determining the propensity to trust Those with a higher education (post-18 years old) are more likely to be classified as trustful. On the other hand, those who left school earlier (15 years old or younger) have a higher chance of being disheartened, everything else being equal
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At the beginning of the survey, a Polish citizen with a master's or bachelor's degree was more likely to be trustful and less likely to be indifferent than someone who left school after only the compulsory education
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Furthermore, Polish citizens with a master's or bachelor's degree are less likely to remain disheartened than those who have only attended compulsory school, all the other characteristics being equal
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Those with education beyond the age of 18 are more likely to become trustful, even if they were previously distrustful or indifferent, compared with those who attended only compulsory education
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The results suggest that citizens will become more and more selective in the future, and unconditional trust will diminish. In particular, highly-educated and married people living outside the cities will increasingly select trusted institutions
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It should be noted that sometimes people may become selective, distrustful, or indifferent because they have been disappointed by certain institutions over time
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Thanks to statistical models like the one used in this research, it is possible to analyze other topics such as opinions towards mass media or artificial intelligence. These topics should increasingly be discussed as the focus of passionate and honest debate
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FULVIA PENNONI
is Associate Professor of Statistics at the University of Milano-Bicocca (Italy). She received her Ph.D. in Statistics from the University of Florence in 2004. Her research is on the interface between the development of statistical models and their application in the social sciences. On the topic of latent variables models, she is the author of two books and she has key publications in refereed international statistical journals.
a.k.a. Irene Rutigliano was born in 1996 under a pile of comics and with her hair already dyed blue. During her first years of life she feeds herself only when hypnotized in front of her VHS of recorded advertisements. Little surprise she then graduated, many years later, in Graphic Design & Art Direction. A professional creative over-thinker, she doesn't know if she should call herself an illustrator: what she is sure of is that engaging people by telling stories and helping them tell their own is what she wants to do in life, and what makes her happiest.
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REFERENCES
[1] Lazarsfeld, P., The logical and mathematical foundation of latent structure analysis, (Princeton University Press, Princeton, 1950) [2] Pennoni, F., Genge, E., Analysing the course of public trust via hidden Markov models: a focus on the Polish society. Statistical Methods and Applications, 29, 399–425 (2019) https://link.springer.com/article/10.1007/s10260-019-00483-9 [3] European Commission, Ethics guidelines for trustworthy AI. (High-Level Expert Group on Artificial Intelligence (AI HLEG), Luxembourg: Office for Official Publications of the European Communities, 2019) https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai [4] European Commission, Public opinion in the European Union. (Standard Eurobarometer, Luxembourg: Office for Official Publications of the European Communities, 2014) https://ec.europa.eu/commfrontoffice/publicopinion/archives/eb/eb81/eb81_publ_en.pdf [5] Bartolucci, F, Farcomeni, A., Pennoni, F., Latent Markov models for longitudinal data, (Chapman & Hall/CRC, Boca Raton, 2013) https://www.routledge.com/Latent-Markov-Models-for-Longitudinal-Data/Bartolucci-Farcomeni-Pennoni/p/book/9781439817087