MAPPING AND EXPLAINING THE DEVELOPMENT OF PUBLIC TRUST IN THE EU DURING THE COVID-19 PANDEMIC - DIVA-PORTAL

Mapping and Explaining the
 Development of Public Trust in
 the EU during the Covid-19
 Pandemic

 Sarah Grudzinski

International Relations
Dept. of Global Political Studies Bachelor program – IR103L
15 credits thesis
Thesis submitted: Spring 2022
Supervisor: Michael Strange

Sarah Grudzinski 20010827T008

 Abstract:

 This study seeks to advance the understanding of the development of public trust in the EU
during the Covid-19 pandemic (from its beginning to March 2022). The importance of this
study lies in the relevance of public trust in institutions in impacting their legitimacy and
success, e.g. of policies. It is found that the EU has lost trust during the pandemic among a
majority of especially central- and Northern- European member states. Four factors relating to
public trust, namely trust in national governments as well as the vaccine, perceived job
insecurity, and the receiving of additional financial aid from EU institutions were explored as
potentially correlating variables in a mixed-method multi-stage research design. Based on the
Eurofound data set titled “Living, Working and Covid-19 Data”, a high substantive but
negligible statistical significance was identified regarding all four variables. In narrowing in on
the negative outlier cases Austria and Germany through newspaper analysis, a correlation
between the sentiment of newspaper reportings and the development of public trust was
identified and the statistical findings were strengthened for all variables but trust in the vaccine.

Keywords: Public trust, European Union, Covid-19 pandemic, support for political
institutions, global governance

Word Count: 13553

Sarah Grudzinski 20010827T008

Table of Contents
Figures and Tables ...............................................................................................................................

Glossary................................................................................................................................................

1 Introduction ..................................................................................................................................... 1

2 Research Purpose and Research Question....................................................................................... 2

3 Literature Review and Theory......................................................................................................... 3

 3.1. Public Opinion and Political Trust .......................................................................................... 3

 3.2. Pandemics and Trust in Political Institutions .......................................................................... 4

 3.3. The EU’s Pandemic Management during Covid-19 ............................................................... 5

 3.4. Summary and Research Gap ................................................................................................... 7

4 Research Design .............................................................................................................................. 9

 4.1. Hermeneutical Discussion ....................................................................................................... 9

 4.2. Multi-Stage Mixed-Method Approach .................................................................................... 9

 4.3. Critical Case Design .............................................................................................................. 10

5 Method and Material ..................................................................................................................... 11

 5.1. Quantitative Data Analysis (Stage one) ................................................................................ 11

 5.2. Newspaper Analysis (Stage two) .......................................................................................... 15

6 Findings and Analysis ................................................................................................................... 19

 6.1. Mapping the Development of Public Trust in the EU ........................................................... 19

 6.2. Establishing correlating factors to the development of public trust ...................................... 20

 6.2.1. Correlation Analysis ....................................................................................................... 21

 6.2.2. Newspaper Analysis ....................................................................................................... 25

7 Discussion ..................................................................................................................................... 39

8 Bibliography .................................................................................................................................. 42

9 Appendices .................................................................................................................................... 50

 9.1. Empirical background ........................................................................................................... 50

 9.2.Figures and Tables ................................................................................................................. 56

 9.3. List analyzed newspaper articles ........................................................................................... 69

Sarah Grudzinski 20010827T008

 Figures and Tables
Fig_ 1 Overview of central EU actions during Covid-19: 2019 to date 50-55

Fig_2 Coding Variables Correlation Analysis 56-58

Fig_3 Comparison Kronenzeitung & Süddeutsche Zeitung 17

Fig_4 Coding Newspaper Analysis 18

Fig_5 Map development trust EU 20

Fig_6 Significance Outlier Cases 59

Fig_7 Contingency Table H1 21

Fig_8 Contingency Table H2 21

Fig_9 Contingency Table H3 22

Fig_10 Strength substantive relationship (Cohen, 1988) 59

Fig_11 Interpretation of substantive significance 60

Fig_12 Interpretation p-value (Wassermann) 60

Fig_13 Mean H4 one-sample t-test 24

Fig_14 Correlation trust vaccine and trust EU (March 2021) 25

Fig_15 Content newspaper reporting 26

Fig_16 Sentiment headlines Kronenzeitung 61

Fig_17 Sentiment headlines Süddeutsche Zeitung 62

Fig_18 Sentiment text of both newspapers 62

Fig_19 Weighing negative and positive sentiment reporting 63

Fig_20 Public trust & Kronenzeitung reporting 28

Fig_21 Public trust & Süddeutsche Zeitung 28

Fig_22 Overview sentiment Kronenzeitung 63

Fig_23 Overview sentiment Süddeutsche Zeitung 63

Fig_24 Kronenzeitung H1 64

Fig_25 Trust national government (Kronenzeitung) 30

Sarah Grudzinski 20010827T008

Fig_26 Süddeutsche Zeitung H1 64

Fig_27 Kronenzeitung H2 64

Fig_28 Kronenzeitung H3 65

Fig_29 Süddeutsche Zeitung H3 65

Fig_30 Kronenzeitung H4 65

Fig_31 Süddeutsche Zeitung H4 66

Fig_32 Map vaccination rollout EU 38

Fig_33 Data development trust EU 67

Fig_34 Overview statistical data 68

 Glossary

 C1/ C2/ C3 Category one, category two, category three

 Df Degree of freedom

 ECSC European Coal and Steel Community

 EU European Union

 H1 / H2/ H3/ H4 Hypothesis one, hypothesis two, hypothesis three, hypothesis four

 IR International Relations

 MMR Mixed method research

 MS Member states

 Fig Figure

Sarah Grudzinski 20010827T008

 1 Introduction

 The Covid-19 virus that was first identified in December 2019 and escalated into a global
pandemic recognized by inter alia the WHO has been described as “the biggest crisis witnessed
by this generation (…) (with) the disruption to normal life (..) bee(ing) on an unprecedented
scale in recent times” (Sud et al 2020). The EU, battling to mitigate the impacts of the pandemic,
took on an important role for member states (MS) during the crisis, as the EU can be viewed as
a crucial mitigation actor regarding the impacts of Covid given that “(t)here are limits to what
decentralized action can achieve against a virus that respects no borders” (Bongardt and Torres
2020:130). The EU’s agency during the pandemic became visible e.g. in the EU funding
research for vaccines, the introduction of the EU-Covid passport, and the imposing and lifting
of travel restrictions (Council of the EU and European Council 2022). The impacts of the
pandemic on the EU and its pandemic management have been identified and discussed in
various scholarly literature, with the findings being based mainly on qualitative analysis and
case studies, concerning e.g. EU competition law (Costa-Cabral et al 2020), health measures
undertaken by the EU (Brooks and Geyer 2020; Cavaleri et al 2021) and the EU’s economy
(Cavaleri et al 2021; De Vet et al 2021).

 However, how said EU measures were judged by citizens and how public trust in the EU
has developed during the pandemic given these measures has remained largely under-analyzed.
This relationship, however, is highly relevant for International Relations, as trust is an important
measure of support for the EU and prospects of European integration, as it affects public support
for institutions, their policies’ successes (Brosius et al 2019; Fukuyama 2020) and their
legitimacy (Hough et al 2010; Jackson and Gau 2016). Previous studies, such as the Eurofound
Report have shown changes in public trust during the pandemic using quantitative methods
(Eurofound 2020). These findings and the EU’s active role in pandemic-mitigation highlight
the relevance of this paper in exploring the development of public trust and potentially
explanatory, correlating factors.

 To fulfill this thesis’ aim of advancing the understanding of the development of public
trust in the EU and correlating factors during the Covid-19 pandemic, a two-stage research
design is employed. Firstly, the development of trust in the EU during the pandemic is
analyzed based on available quantitative data. Secondly, the negative outlier cases in which
trust in the EU has decreased most starkly are further examined during a newspaper analysis.
This is done to understand the role of newspapers in bridging the communication gap (Heise
 1

Sarah Grudzinski 20010827T008

1985) between institutions and the public, influencing public trust in institutions, and to
substantiate the statistical findings. The factors to be inspected are decided upon based on
previous literature establishing their relevance, a correlation analysis of the quantitative data
disclosing substantive significance, and broader categories assigned to the most relevant EU
actions taken during the pandemic.

 This research puzzle is highly relevant for the academic realm of International Relations not
only because of the EU’s role as a transnational institution of governance with supranational
features situating this paper within the academic realm of IR, but also because Covid-19 links
to and shapes a variety of IR processes including global governance, regional integration, and
international policymaking. Hence, discussions surrounding the impact of Covid on public trust
in institutions can be viewed as a central, timely academic debate within the realm of
International Relations. The choice of a multi-stage mixed-method research design might be
able to generate new insights and, hence, constitute a valuable addition in providing grounds
for comparisons to the existing quantitative case study designs with more narrow focuses.

 2 Research Purpose and Research Question

 This research seeks to outline and advance the understanding of the development of trust of
citizens of EU member states (EU MS) in the EU during the Covid-19 pandemic. The
achievement of this research aim requires the answering of two working questions:

Firstly, how has public trust in the EU developed among citizens of EU MS during the Covid-
 19 pandemic?

 Secondly, which potentially explanatory correlating variables link to the development of
 public trust in the EU?

 2

Sarah Grudzinski 20010827T008

 3 Literature Review and Theory

 The following section aims to outline relevant literature on public opinion and political trust,
pandemics and trust in political institutions, and the EU’s pandemic management during Covid-
19. To analyze the development of public trust, one first must understand what the term entails,
why it is relevant and which factors have been found to influence it. More specifically, the
second sub-section of the literature review narrows in on how pandemics affect public trust, as
those pose an exceptional situation impacting all aspects of public and institutional agency and
hence, a variety of specific factors exclusive to those states of exception are to be considered.
Thirdly, analyzing how public trust in the EU has developed requires an understanding of the
EU’s actions during the pandemic. Specifically, two highly visible spheres of EU action during
the pandemic, namely the economic sphere and vaccines are further discussed.

 Throughout the literature review, the relevance of factors treated as independent variables in
the correlation analysis, namely trust in national governments and the vaccine, perceived job
insecurity, and the receiving of additional financial help from EU institutions is highlighted.
Hence, the following section lays the foundation for the analysis in contextualizing, explaining,
and highlighting focus areas that are central for the formulation of the hypotheses explored in
the correlation analysis during stage one and the coding process of the newspaper analysis
during stage two.

 3.1. Public Opinion and Political Trust

 Political trust is both “the glue that keeps the system together and (…)

 the oil that lubricates the policy machine” (Van der Meer, 2010, 76).

 In alignment with this quote, previous literature has found trust to be highly relevant for the
establishment of support for institutions, their policies’ successes (Brosius et al 2019;
Fukuyama 2020), and their legitimacy (Hough et al 2010; Jackson and Gau 2016). The
importance of trust in institutions is partially due to its fundamental character in being “directed
to basic aspects of the system” (Easton 1975:437) and its function in reducing the transaction
costs of policymaking and solving collective action problems (Hartevelt et al 2013). Given its

 3

Sarah Grudzinski 20010827T008

relevance, trust has been widely debated in the academic political realm. The concept of trust
in political institutions is highly complex and a variety of factors influencing trust in
institutions, such as an individual’s values (Van der Meer and Hakhverdian 2017), subjective
evaluation of the institutions’ performance (Brosius et al 2019), personal circumstances
(Hudson, 2006) and trust in respective national institutions (Aksoy et al 2020; Dellmuth and
Tallberg 2015) have been identified.

 Given the extent of the academic debate on the role of trust relating to political institutions,
it is unsurprising that conceptualizations and theories on the role of trust vary also: Brosius et
al (2019) conceptualize trust as “a measure of generalized institutional support”. Hartevelt et al
(2013) found the logic of extrapolation, which theorizes trust in the EU as an extension of
national trust, to be the highest predictor of trust in the EU when compared to the logic of
rationality, which explains trust as resulting from citizens’ rational evaluations of the EU’s
performances, and identity trust, which focuses on the component of emotional attachment
towards the EU. Aksoy et al (2020) on the other hand have found that trust in the EU might
increase among citizens with low trust in their respective national governments because the EU
can “function as a potential lifebuoy” in providing them with potentially better governance.
Which theory best explains the case at hand is elaborated on in the discussion section.

 3.2. Pandemics and Trust in Political Institutions

 Another factor influencing trust in political institutions as identified by previous literature
and highly relevant for this research is the state of exception induced by pandemics. There is a
growing body of literature documenting correlational evidence that pandemics affect social and
institutional trust. Brück et al (2020) conducted a global survey and uncovered a negative
correlation between exposure to (people infected with the) Covid-19 virus and interpersonal
and institutional trust. More specifically, Aksoy et al (220) found that the decrease in trust in
institutions witnessed during the pandemic is particularly high among younger individuals
between the age of 18 and 25. The correlation between low trust in political institutions and
public health during a pandemic seems to not be exclusive to Covid-19, having been identified
also during the Spanish flue pandemic of 1918 (Aassve et al 2020) or the Ebola outbreak in
Liberia as found based on a large-N survey (Blair et al 2017). Note, that these correlations have
been established between the public and national-level authorities and institutions. Whether the

 4

Sarah Grudzinski 20010827T008

same phenomenon of decreasing institutional trust applies to the EU’s pandemic management
is part of the puzzle this paper seeks to answer.

 3.3. The EU’s Pandemic Management during Covid-19

 When Covid first emerged, it started as a health crisis. Given its quick spread and
comparably high death rates, it quickly was politicized as many countries went into lockdowns
and gradually closed down the public sphere. This political reaction produced consequences
also in the economic sector, with production rates declining and unemployment rates inclining,
which, in turn, furthered a societal crisis with increasingly many individuals being dependent
on aid. This is to say that “(e)very single policy area already in crisis was affected, including
eurozone and migration policy, and many of those with seemingly settled policies and politics
were also disrupted, such as in competition policy and health policy” (Schmidt 2020).
Generally, the Covid-19 crisis has been framed as “existential” for the EU (Russack and
Blockmann 2020:2).

 Previous scholarly discussions have found that internal cohesion is one of the key challenges
for the EU and highly significant for the prospect of European integration (Bachtler and Mendez
2016; Baun and Marek 2014; Marks et al 1996; Leonardi 2005). However, during the pandemic
“EU actors held divergent perceptions of what should be done, undergirded by conflicting
philosophies, divided preferences, and divergent policy ideas” (Schmidt 2020). In addition to
different perceptions regarding best strategies, national responses were “uncoordinated”
(Bongardt and Torres 2020:130) and hence, “threaten(ed) core European institutions” (ibid).
However, there is a certain duality found in the literature in that Covid could pose as an obstacle
or “an opportunity to advance integration and reinforce EU objectives”(ibid): “EU governance
in the Covid-19 crisis may very well result in paradigmatic change towards deeper European
integration (…) or even reversal toward dis-integration” (Schmidt 2020). While some of the
EU’s most visible features such as free trade and mobility (Recci and Favell 2009) were hit by
the pandemic, the EU’s agency and actions have also been highly visible in daily life e.g.
regarding the EU’s Covid passport, financial support measures to member states and the EU’s
approval and distribution of the Covid vaccines.

 For example, concerning the EU’s economy, Covid can be seen as having “illustrated the
fragility of European common goods like the single market and the Schengen agreement and
even the Economic and Monetary Union” (ibid), but also as an opportunity: This is, as the EU

 5

Sarah Grudzinski 20010827T008

has taken central measures in mitigating the infection rates, coordinating national responses,
and managing the overall impacts of Covid-19 during the pandemic e.g. by subsidizing
businesses.

 When considering the EU’s most central decisions and actions taken to mitigate the Covid
pandemic and its impacts as published by the European Council and Council of the EU (2020),
two central areas, namely the economy and vaccine policy, are most prominent. Note, that Fig_1
in the Appendix provides the empirical background for the following discussion in displaying
an overview of the most relevant Covid-19 mitigation efforts realized by the EU.

 Firstly, with the EU’s foundation being an economic union (ECSC) and with its most visible
and well-known features being the free trade bloc with the Euro as its single currency, the
economic features of the EU can be considered highly relevant also for citizens’ understanding
of the EU. However, the EU’s trade policy was impacted by Covid inter alia in the closing of
external and internal borders, layoffs, and the (partial) closing of the public sphere. As the
workplace provides the only source of income for most individuals and their dependents (Keim
et al 2014; Wilson et al 2020) and most workplaces were affected by the pandemic, perceived
job insecurity is an important consideration to make when analyzing public trust in the EU from
an economic perspective. During Covid, “many countries adopted social distancing and
lockdown policies, and many businesses and services were closed or suspended, which resulted
in historic numbers of furloughs and layoffs worldwide” (Fouad 2020; Hamouche 2020;
Restubog et al 2020; Sergent and Stajkovic 2020 in: Lin et al 2021), which did not only affect
unemployment rates but also perceived job security among those who remained employed. The
development of perceived job security during Covid is highlighted inter alia in the Eurofound
Report, identifying an increase in perceived job insecurity between the beginning of the
pandemic and Spring 2021 (Eurofound Report 2020:2).

 Previous scholarly findings vary on the role of the economic aspect relating to public trust
in the EU and citizens’ perceptions of it: “(After the early 1990s), GDP or unemployment rates
no longer influenced EU support” (Brosius et al 2019). Koehler et al, on the other hand, found
that “in regions where unemployment is higher, citizens support the EU more, indicating that
citizens may see the EU as the solution rather than the problem in some cases” (Koehler et al
2018). Hudson presents contradictory findings to Koehler et al, in that “unemployed people
tend to have lower levels of trust (…) in (…) state institutions” (2006). Given these
contradictory scholarly findings and the EU’s active role in mitigating inter alia the economic
impacts of Covid-19 (see: Fig_1), it is important to consider the potential correlation between

 6

Sarah Grudzinski 20010827T008

perceived job insecurity and public trust in the EU. One of the pointed actions realized by the
EU in mitigating the economic effects of Covid-19 is the distribution of financial support e.g.
in the context of the SURE initiative (See: Fig_1), during which some EU member states
received additional financial relief packages. “Earlier analyses found that receiving financial
support has a positive impact on levels of trust in the government and trust in the EU”
(Eurofound report 2020:16). Hence, one could expect that trust among citizens of EU MS that
have received financial support from the EU during Covid increases or is comparatively higher
than the trust of citizens of EU MS that did not receive financial support from the EU.

 Secondly, vaccine policy: Given the EU’s agency in coordinating vaccine development and
the approving, purchasing, and distributing of the vaccine, this factor is highly relevant when
discussing the EU’s Covid-mitigation efforts and the public’s perception of these. Previous
studies have discovered a correlation between mistrust in institutions and authorities and
vaccine hesitance concerning Covid-19 (Bogart et al 2021; Heyerdahl et al 2022; Recio-Román
et al 2021). For example, Recio- Román et al found a positive correlation between vaccine-
hesitance and political populism with the mutual driver of “distrust in institutions, elites, and
experts” (2021). Given the EU’s relevance in decision-making concerning vaccinations and the
previous findings, the correlation between trust in the EU and trust in the vaccines is to be
further explored.

 3.4. Summary and Research Gap

 Previous literature has highlighted the relevance of public trust in institutions, as an
institution’s legitimacy and success (e.g. policy success) are impacted by the levels of public
trust (Brosius et al 2019; Fukuyama 2020; Hough et al 2020; Jackson and Gau 2016), which
substantiates the relevance of this study.

 The case at hand, namely the development of public trust in the EU during the Covid-19
pandemic has been previously addressed with the focus being set on various specific aspects,
such as vaccine policies (Recio- Román et al 2021), regulatory decision-making (Dal-Ré and
Launay 2021) or specific national contexts (e.g. Warren et al 2021; Kukovič 2021).
Additionally, the role of media coverage in shaping public attitudes towards the EU has been
previously explored (Brosius 2020; Brosius et al 2019) inter alia through employing the method
of media analysis in various specific contexts such as e.g. the framing of the migration crisis
(Brosius et al 2019) or economic news (ibid).

 7

Sarah Grudzinski 20010827T008

 While theories on public trust in the EU vary as outlined above, it has been established that
pandemics generally impact trust in national-level institutions negatively. Furthermore, a
variety of influential factors on the development of public trust, such as trust in national
governments (Aksoy et al 2020; Brosius et al 2019), vaccine hesitancy (Bogart et al 2021;
Heyerdahl et al 2022; Recio-Román et al 2021), financial aid, and perceived job insecurity
(Eurofound Report 2020; Koehler et al 2019) have been identified.

 The previous findings were established based on a variety of quantitative and qualitative
data, employing various methods like textual analysis (e.g. Costa-Cabral et al 2020) including
process tracing (e.g. Cavaleri et al 2021) and policy analysis (e.g. Brooks and Greyer 2020),
mixed-method approaches (e.g. De Vet et al 2021, Van der Meer and Hakhverian 2017) and
statistical analysis (e.g. Brosius et al 2019; Recio-Román et al 2021).

 While contributing valuable insights into the respective academic debate, the previous
narrow study designs caused by e.g. a specific policy focus, country selections, or methodology
have established individual correlating factors but not provided a more general picture of how
public trust in the EU develops or what influences said development.

 This research expands the existing knowledge in two ways: Firstly, this study seeks to
establish whether the previously identified variables are also relevant for the case at hand and
hence, involves a theory-testing aspect. Secondly, in including more than one potentially
influential variable on the development of trust, this study might disclose relevant implications
for discussing public trust in general. This is as the degree of correlation between independent
variables and public trust and whether causalities can be identified is highly relevant when
discussing public trust, as they potentially inhibit the operationalization of public trust in that
(un-)known confounders i.e. the correlating variables cannot be accounted for. This implies that
discussions regarding the development of public trust are conflated by a variety of correlating
variables/ confounders and hence, a new approach to grasping public trust would be
necessitated.

 8

Sarah Grudzinski 20010827T008

 4 Research Design
 4.1. Hermeneutical Discussion

 Scholars disagree on the relevance of hermeneutical discussions for mixed-method research
(MMR) designs. While it has been argued that different paradigms exist within MMR (Alise
and Teddlie 2010; Creswell and Tashakkori 2007; Denscombe 2008; Sommer Harrits 2011)
and hence, their discussion is relevant for the internal validity of the study, others view MMR
to transcend existing paradigms (Felizer 2010; Johnson et al 2007; Morgan 2007; Scott and
Briggs 2009). Given that this scholarly discussion cannot be analyzed given the scope of this
paper and based on the argument that “ ‘MMR is strictly a method’ (and) thus allow(...)(s)
researchers to employ any number of philosophical foundations for its justification and use“
(Creshwell and Plano Clark 2007:27) the following paragraph discloses this papers’
ontological end epistemological assumptions.

 This paper’s research question concerns itself with how popular trust in the EU has
developed and which factors correlate with and potentially influence said development. Hence,
the underlying ontological assumptions are subjectivist, as the central focus of this study lies
with individuals’ perceptions and how they make sense of the EU and its actions. This
subjectivist-leaning underlying ontological position informs the epistemological approach to be
interpretivist. The multi-stage mixed-method approach is the chosen methodology given its fit
in answering the research question which has informed the ontological and epistemological
approach and hence, is in line with the taken hermeneutical position.

 4.2. Multi-Stage Mixed-Method Approach

 This research design employs a multistage mixed-method approach based on a
supplementary and theory-testing design. The theory-testing character is based on the analysis
of potentially influential factors correlating to public trust in the EU (as outlined in the
hypotheses). The multistage and supplementary aspects are clustered into two phases of the
research process: The first stage aims to map the development of trust of EU MS citizens’ in
the EU based on quantitative data (until March 2021) that seemingly grasps public trust. Under
the given time frame (from when Covid emerged to March 2021), the population of interest is
defined as all citizens of EU MS. The second stage narrows in on the sub-group of the negative

 9

Sarah Grudzinski 20010827T008

outlier cases Austria and Germany to supplement findings on factors relevant to the
development of public trust in the EU within an expanded temporal dimension to include more
recent developments as well as the aspect of newspaper reportings.

 Employing a multi-stage mixed-method research design is beneficial for this study, as the
original target population is too broad to analyze and the studied phenomenon is as complex as
public trust with a variety of external factors having been shown to influence it. Furthermore,
given the timeliness of the Covid-19 pandemic, this study, while significantly contributing to
relevant academic discussions surrounding the topic at hand, faces the difficulty of limited
available data. For example, the Eurofound data set analyzed at stage one ends in March 2021.
While the analysis conducted during stage one is valuable in itself given the novelty of this
research, employing a multi-stage mixed-method research design and considering different
types of data and methods allows the studying of more recent developments and to more
accurately grasp how academia studies public trust. Hence, the supplementary stages pose the
best methodological fit to answer the research question at hand.

 4.3. Critical Case Design

 A critical case design is chosen with “the facts of the case (…) (being) central to the
confirmation or disconfirmation of a theory” (Gerring 2007:231) during the second stage of the
research design. The following two reasons justify the choice to analyze the critical cases:

 Firstly, given the absence of equidistance, smaller changes in the development of public trust
were potentially caused by said absence or the lack of defining categories for the measurement
of the scale, which poses an obstacle to fulfilling the research aim. Secondly, given the theory-
testing dimension of this research design, the choice to analyze the outlier cases best fits the
research aim, which is the establishing of potentially influential factors on public trust in the
EU. The influence of the independent variables was likely to be most stark among the outlier
cases and hence, more identifiable among countries in which the changes in the levels of public
trust were more significant.

 More specifically, the choice to analyze the negative outlier cases of Austria and Germany
was made. This is as previous literature has already addressed the trust gain in the positive
outlier cases and provided explanations such as the dissatisfaction with one’s national
government leading to increased trust in the EU based on hope for “better governance” at the
EU level (Eurofound 2020; Aksoy et al 2020). However, there is a gap identifiable among

 10

Sarah Grudzinski 20010827T008

previous literature addressing the negative outlier cases, which makes the findings addressing
the negative outlier cases a more significant contribution to the academic debate. The
significance of the outlier cases is illustrated in Fig_6 in the Appendix, which shows how much
more starkly trust has developed among the outlier cases compared to the average development
in the respective category established in Fig_2 and the average development when clustering
the countries according to general trust in-/decrease. Therefore, and in line with previous
findings, the negative outlier cases can be assumed to facilitate a larger influence of external
factors besides trust in national governments given the scope of changes in trust levels, which
fits the theory-testing aspect of this study. Additionally, the practicality of language proficiency
becomes relevant when analyzing newspaper publications, as high proficiency encourages the
required nuance. Given the researcher’s native language proficiency in the German language,
the analysis of the negative critical cases ensures the required nuance and cultural understanding
relevant for internally valid textual analysis.

 5 Method and Material
 5.1. Quantitative Data Analysis (Stage one)

 To establish trends in the development of trust in the EU among citizens of EU MS, the data
set titled “Living, working and Covid-19 data” which was published by the Eurofound database
was analyzed. The dataset is based on a survey encompassing a variety of aspects of life during
Covid, including those at the heart of the hypotheses whose relevance was outlined during the
literature review. The survey was of a descriptive nature, which is to say that it does not “suggest
causality” (Jann and Hinz 2017:106). The Eurofound database’s data collection process
consisted of three rounds during which the online survey was published, with round one taking
place in April 2020 “when most Member States were in their first lockdown” (Eurofound
Report 2020:14), round two in July 2020 “when economies and societies were gradually
reopening” (ibid) and round three in March 2021 “as countries were still dealing with various
levels of lockdown (and) problems with the vaccines began appearing in the media” (ibid). The
survey was open for citizens of EU MS over the age of 18 and the snowball sampling technique,
as well as advertisements on social media, were being employed as methods of data collection.

 Note, that one unit of observation, here one individual, does not constitute one unit of
analysis (Jann and Hinz 2017:4), as the latter is defined as one EU MS in this study. The
descriptive survey was operated under a longitudinal design used to “examine changes over

 11

Sarah Grudzinski 20010827T008

time” (ibid). More specifically, a trend design was employed, which “comprises a series of
cross-sectional studies in which the same questions are administered to independent samples
from a population at different points in time” (ibid:112), as country-specific means based on
individual responses measured on a scale from one to ten were generated at different points in
time. Note, that this scale is ordinal, which means that each value represents a different extent
of an individual’s perception regarding each question, which can be ranked from smallest to
most, but are not equidistant, as the results are based on individuals’ perceptions.

 For ordinal scales, mode and median are the most important levels of measurement and
central tendency to consider (Lewis-Beck 1995), but the given data set contains the means. For
the data analysis, this results in the absolute value of the obtained means being inhibited in their
meaningfulness. Therefore, and given that the trends and development of the trust in the EU are
of interest when answering the first working question, the data is processed into 15 scenarios
based on trends in development (see: Fig_4). Therefore, the variables trust in the EU, trust in
national governments, and perceived job insecurity are categorical variables which means that
they are “measured only in terms of whether the individual items belong to certain distinct
categories, but we cannot quantify or even rank order the categories” (Kaur 2013:37).

 The numeric independent variable “trust in vaccine” was measured in percentages and hence
is ratio data, as percentages allow for equidistance and a zero value exists. The independent
variable of receiving additional financial support from the EU is categorical and binary, as it
was grasped based on the receiving of additional funds during the SURE initiative. The SURE
initiative is chosen, as it was the biggest distribution of additional financial aid from EU
institutions in which only some specific members received additional funds from the EU during
the time analyzed. The variable grasping the receiving of additional financial aid is coded in
the following way: The value one represents the receiving of funds within the SURE initiative
and zero means that a county has not received any funds within that initiative. Analyzing the
country allocation for the coded categories one to six (based on Fig_2) provides an overview
of the development of trust in the EU during the pandemic in the given timeframe.

 The following section argues the fit of the chosen methodology to answer working question
one while also considering the limitations inherent to the analyzed data. Note, that the first
working question concerned with the development of public trust in the EU holds some
descriptive characteristics. “For descriptive studies, external validity in the sense of
generalizability from the sample to the population is of great (...) concern” (Jann and Hinz
2017:111).

 12

Sarah Grudzinski 20010827T008

 Two aspects of the survey design infringe the survey’s generalizability, namely the
employed sampling method being snowball sampling, and the response numbers. Firstly, note
that the employed sampling method of “(s)nowball sampling faces some criticisms. (It is often
employed) where generalization, representativeness, and external validity are not sought after”
(Parker et al 2019). Secondly, note that the sample population does not achieve the required
size for a statistically relevant sample according to Yamane’s formula to calculate the minimum
response numbers (Yamane 1967:886):

 445000000
 = = = 399,9994
 1 + (ⅇ)2 1 + 445000000(0,05)2

 Based on the Central Limit Theorem, the 95% confidence level is chosen (e= 0,05), as it is
the one conventionally used in political sciences (Yin 2017:68) to measure whether the
observed relationships are statistically significant. According to Eurostat, the population of the
EU based on the last obtained data (February 2020) encompasses 445 million people (N). The
required sample size (n) not being achieved by the Eurofound data set limits the internal validity
and generalizability of this research.

 However, given that the target population is defined as all EU citizens over the age of 18
during stage one, it is highly unlikely for researchers to achieve the required sample size as
calculated by Yamane, especially when adding further considerations required by other
sampling techniques. Given the lack of alternative data and based on this study’s relevance
amid the ongoing pandemic, it is argued that the collected data still holds some merit and
generalizations can be drawn. This is, as other respected IR research (e.g. the Eurofound report
2020) has been conducted based on the given data set, and hence, further contributions to the
current scholarly debate are relevant.

 Hence, this research can be viewed to achieve copacetic external validity, which can be
triangulated by future research due to this study’s high reliability. Furthermore, despite the
previously outlined limitations and the temporal delimitation, this data contributes to answering
the research puzzle in two manners: Firstly, the dataset includes country-specific questioning
of all 27 EU MS, and hence, allows the grasping and comparing of citizens’ perceptions, which
is relevant when analyzing subjective variables such as trust. Secondly, the data offers some
insight into factors influencing citizens’ trust in the EU, which is relevant for the answering of
the second working question, as it includes data on factors established as relevant in previous
literature.

 13

Sarah Grudzinski 20010827T008

 Having discussed the data and its methodological fit, the following paragraphs discuss the
statistical analysis employed when analyzing the data in answering working question two.
Running a correlation analysis based on the quantitative data set generates some insights into
potentially correlating factors influencing the development of public trust in the EU. Correlating
the established country-specific scenarios of the dependent variable (see: Fig_2) with the
respective independent variables helps answer which external factors influence the
development of public trust in the EU and hence, the second working question.

 This is done by running the Cramer’s V test of association and the Chi-square test in Python
for the hypotheses one to three. These correlation tests are chosen as they are best suited to
correlating the respective types of variables at hand: “A chi-square test is used to examine the
association between categorical variables” (Waller and Johnson 2014:2). It “is used to
determine whether the association between two variables is significant, with the null hypothesis
being that the two variables are not dependent on one another” (Kearney 2017:2). The Cramer’s
V test is a T-test that is “used to examine the differences between means” (Waller and Johnson
2014:2) and to “measure the association between categorical variables that include more than
two levels” (Kearney 2017:3).

 Both tests are run, as the Chi-square test outputs the statistical significance of the correlation
analysis, answering the question of whether the “variation (is) great enough (…) to place some
confidence in the result” (Kish 1959:336) and the chosen T-test outputs the substantive
correlation disclosing whether “the result show(s) a relationship which is of substantive interest
because of its nature and its magnitude” (ibid). The chosen tests are of the best fit for the
correlation analysis, given that the dependent variable “public trust in the EU” is categorical,
rendering other correlation tests such as Pearson, point-biserial, or correlation ratio unfit. For
hypothesis four, the independent variable is numeric and non-binary, and therefore, a one-
sample t-test that analyzes the mean and average distribution is run. Python is chosen as
operating software, as it allows for the correlating of categorical variables and was able to
conduct the Cramer’s V T-test and the Chi-square test.

 To run the correlations outlined above, the following hypotheses are established:

 H1: The level of trust of citizens of EU MS relates to citizens’ trust in their respective
 national governments.

 H10 : ≠ 0 is tested against H1: = 0

 H2a: The level of trust of citizens of EU MS relates to citizens’ perception of job security.

 14

Sarah Grudzinski 20010827T008

 H20 : ≠ 0 is tested against H2: = 0

 H3a: The level of trust of citizens of EU MS relates to the receiving of financial aid from
 EU institutions.

 H30 : ≠ 0 is tested against H3: = 0

 H4a: The level of trust of citizens of EU MS relates to citizens’ trust in Covid-19 vaccines.

 H40 : ≠ 0 is tested against H4: = 0

 5.2. Newspaper Analysis (Stage two)

 Having explained the choice to analyze the critical cases of Austria and Germany (see: 4.3.
Critical Case Design), a textual analysis of newspaper articles of the biggest newspapers in
Austria and Germany is conducted. Previous scholarly literature has distinguished newspapers
based on their defining features of regular publications, constant readership, and a “more or less
standard format” (Woodward 1934). The central functions of newspapers have been
characterized as informative (Druckmann 2014; Schmidt 2005), e.g. in bridging the
“communication gap” between institutions and the public (Heise 1985) but also as opinion-
shaping (Schmidt 2005; Woodwar 1934; Druckmann 2014; Moussaïd et al 2013; Hans-Jörg
Trenz and Rosen, 2007; Stempel 2014). The degree to which scholars attribute opinion-shaping
capacities to newspapers varies in previous literature from laying the foundation for opinion-
forming processes inter alia by providing relevant information and context regarding political
processes, institutions, and news in general (Schmidt 2005) to molding the readers’ opinion
(Woodwar 1934). Woodwar takes on a comparatively extreme position in arguing that
newspapers print what the public wants to read (ibid) and hence, views newspapers to reflect
public opinion.

 Despite varying scholarly positions on the central functions of newspapers in shaping or
reflecting public opinion, a relationship between newspaper reportings and public opinion has
been previously identified: Studies have shown the opinion-shaping capacities of newspapers
e.g. in setting the political agenda through coverage (McCombs 1977; McCombs 2002),
teaching citizens “issue positions (...) (through) mass communications” (Druckmann 2014), and
influencing the publics’ weighing and evaluations of attributes, issue positions or events
(Druckmann 2014; Druckmann 2001).

 15

Sarah Grudzinski 20010827T008

 In addition to these mechanisms and linked to the agenda-setting function of newspapers as
previously discussed, the volume of material printed on certain subjects alone has been found
to influence public opinion (Woodwar 1934; Dalton et al 1998; Levendusky 2009). Note, that
the effects of said relationship have been found to not be ephemeral through the identification
of a lag (Coppock et al 2018; Woodwar 1934) which suggests “underlying attitudinal changes”
(Coppock et al 2018) based on newspaper reporting and highlights the significance of the
relationship between newspaper reporting and public opinion.

 The same characteristics have been attributed to opinion pieces published by newspapers
(Coppock et al 2018; Porpora and Nikolaev 2008; Dalton et al 1998; Moussaïd et al 2013)
through inter alia the expert effect “induced by the presence of a highly confident individual in
(...) (a) group” (Moussaïd et al 2013) and the mass effect “caused by the presence of a critical
mass of laypeople” (ibid).

 Furthermore, the sentiment of the reporting also influences readers’ attitudes (Chong and
Druckman 2011; Levendusky 2009; Druckman et al 2013) e.g. through polarization as
communicated by the media increases constraints (Druckman 2014). As these previous findings
show a correlation between newspaper reporting and the formation of public opinion,
newspaper analysis can generate some insights into how the public opinion and public trust in
the EU have developed and which factors have shaped this development illustrating the
methodological fit of newspaper analysis in answering the research question.

 In this study, one unit of classification equals one article or opinion piece. The articles to be
analyzed are chosen based on two criteria: The first criterion is based on the inclusion of the
key terms “EU” and “Corona” or equivalents (e.g. Brussels for EU) in the (sub-)title, as well as
a reference to the EU, EU policies or EU politicians in the (sub-)title or picture. The second
criterion refers to a temporal delimitation: Articles published between December 1st, 2019, and
March 1st, 2022, which meet the first criterion are included in the analysis and clustered in four
temporal sections with the first three equating the rounds of the Eurofound data collection and
the fourth one tracing the developments since the latest available data gathered by the
Eurofound foundation. Hence, cluster one contains articles published between December 1st,
2019, and April 9th,2020, cluster two between April 10th, 2020, and July 1st, 2020, cluster three
between July 2nd, 2020, and March 1st, 2021, and cluster four March 2nd, 2021 and March 1st,
2022. The temporal delimitation of March 1st, 2022 is caused by practicalities such as the time
needed for the data collection and analysis within the scope of this research project. In total,

 16

Sarah Grudzinski 20010827T008

227 articles published by the Kronenzeitung and 121 articles published by the Süddeutsche
Zeitung are analyzed.

 Based on this reasoning for analyzing newspapers, the circulation and readership size are the
most important criteria when choosing a newspaper to analyze. In Austria, the newspaper with
the highest circulation is the “Kronenzeitung” (Statista 2022) reaching around 11% of the
population. According to Statista, the German newspaper “Die BILD” was the newspaper with
the nation-wide highest circulation, followed by the “Süddeutsche Zeitung” (Statista 2021).
Given that the archive of Die BILD is hidden behind a paywall and hence could not be accessed,
the articles published by the Süddeutsche Zeitung, reaching around 1,2% of the German public,
are analyzed. Note, that despite the high circulation, both newspapers reach only a fraction of
the population based on their readership, which potentially mitigates the validity of the findings.
However, note that both papers are not targeted to a specific audience and similar patterns could
be found in both newspapers, despite significant differences as displayed in Fig_3 below:

 Fig_3: comparison Kronenzeitung & Süddeutsche Zeitung

 This is to say that likely other news channels and information sources aimed at the general
public follow similar trends in reporting. A deductive approach to the newspaper analysis is
chosen as “the structure of analysis is operationalized on the basis of previous knowledge and
the purpose of the study is theory testing” (Kyngäs and Vanhanen 1999:108). Here, the

 17

Sarah Grudzinski 20010827T008

influence of the chosen independent variables on the dependent variable is analyzed. Hence the
coding criteria are chosen per the variables as well as relevant information regarding the
published texts. The coding criteria are displayed in Fig_4 below:

 Fig_4: coding newspaper analysis

 Coding criteria applied to evaluating the negative/ positive/ or neutral sentiments of a text
include the placement of punctuation marks, rhetoric tools like sarcasm or exaggerations, and
the usage of specific value-laden terms. These criteria as well as the evaluations of the
sentiments are established according to Vromen’s micro-concern for linguistics (Vromen
2018:51) based on which attention is paid to rhetoric and the chosen vocabulary. Specifically,
the voiced sentiments are clustered further per the following three categories: Category one
(c1), collects texts that indirectly criticize/ praise a politician, policy, or institution, e.g. through
leading questions. Category two (c2) collects texts containing substantiated critique/
evaluations, e.g. of a specific policy or politician as well as sentiments voiced by a (usually
well-known) speaker. Category three (c3), collects value statements, emotional and
unsubstantiated critiques of entire institutions, individuals, or structures as well as subjective
interpretations of e.g. policy developments. Articles as well as letters to the editors and opinion

 18

Sarah Grudzinski 20010827T008

pieces are included, as both can impact the public perception of an event or institution
(Woodward 1934; McCombs 2002; Hans-Jörg Trenz and Rosen 2007; Stempel 2014).

 6 Findings and Analysis
 6.1. Mapping the Development of Public Trust in the EU

 Note, that the following findings answer working question one, “ How has public trust in the
EU developed among citizens of EU MS during the Covid-19 pandemic?” according to the
existing paradigm on how public trust is operationalized.

 Quantitative data analysis of the Eurofound data set reveals the development of public trust
in the EU in the respective national contexts. Generally, the data shows that trust in the EU has
declined a total of -0,74% among the public of all EU MS during the pandemic (Eurofound
2021), with the summed development of trust having increased from April 2020 (r1) to July
2020 (r2) and decreased from r2 to March 2021 (r3) (see: Fig_33). Fig_2 shows the individual
development of trust in each EU MS, with most EU MS having lost trust in the EU during the
pandemic (Austria, Belgium, Croatia, Cyprus, Denmark, Estonia, Finland, Germany, Ireland,
Lithuania, Slovakia, Bulgaria, Latvia, Netherlands, and Sweden), public trust having increased
in nine EU MS (France, Hungary, Italy, Malta, Poland, Portugal, Romania, Slovenia, and Spain)
and remained at the same level in three EU MS (Czechia, Greece, and Luxembourg).

 A geographic representation of the development of trust below shows, that the EU has lost
trust mainly among central European and Scandinavian member states, while the countries in
which the EU has gained the most trust are situated in the East and South-West of the EU.

 19

Sarah Grudzinski 20010827T008

 Fig_5: Map development trust EU

The critical cases reflect this geographic pattern: The countries in which the EU has gained the
most trust are Spain and Italy in South (-Western) Europe, and Austria and Germany, where the
EU has lost the most trust, are located in the center of the EU.

 6.2. Establishing correlating factors to the development
of public trust

 Having understood how public trust in the EU has developed from round one to round three
during the pandemic, the following section contributes to answering working question two,
namely “Which potentially explanatory variables link to the development of public trust in the
EU?”. Note, that the following section hence establishes which independent variables correlate
to the development of public trust and which variables seem to hold the most significant
influence. In answering working question two, the employed mixed-method and multi-stage
research design facilitates the analysis of statistical as well as textual data and the expansion of
the timeframe under analysis.

 20

Sarah Grudzinski 20010827T008

 6.2.1. Correlation Analysis

 Based on the previously established hypotheses, the following section outlines the findings
of the correlation analysis together with contingency tables, which highlight the frequency
distributions for the independent variables trust in national governments, receiving of additional
funds from the EU, and perceived job insecurity. Public trust in the EU is the dependent
variable.

H1: The level of trust of citizens of EU MS in the EU relates to citizens’ trust in their respective
national governments.

 Fig_7: Contingency table H1

 Cramer’s V: v= 0,43501 Chi square: p= 0,42134

H2: The level of trust of citizens of EU MS in the EU relates to citizens’ perception of job
security.

 Fig_8: Contingency table H2

 Cramer’s V: v=0,59724 Chi square: p=0,010209

 21

Sarah Grudzinski 20010827T008

H3: The level of trust of citizens of EU MS in the EU relates to the receiving of additional
financial aid from EU institutions.

 Fig_9: Contingency table H3

 Cramers’s V: v= 0,51908 Chi square: p= 0,200973

 As outlined in the Method and Material section, the Cramer’s V-test outputs the substantive
significance of a relationship, and the Chi-square test discloses the statistical significance of a
relationship. In other words, the Cramer’s V test shows how strongly the independent variables
addressed by the respective hypothesis correlate with the dependent variable of public trust in
the EU and hence, are substantivally significant. The Chi-square test results disclose whether
the observed changes in public trust are caused by an underlying effect (i.e. the independent
variables) rather than by chance and hence, are statistically significant.

 In interpreting these findings and evaluating the strength of the observed correlations’
significance, it is useful to draw on previous literature in analyzing firstly, the substantive, and
secondly, the statistical significance of the correlations. Recall that Cramer’s v takes on values
between zero and one, with zero being interpreted as no relationship of association and one
indicating a perfect relationship of association. Cohen ranks the obtained values and associates
the respective strength of a correlation under consideration of the degree of freedom, which is
established based on the numbers of rows and columns of the contingency tables (see: Fig_10).

 With the derivations argued in Fig_11, there is a relationship of large substantive
significance identifiable among the independent and the dependent variable in hypotheses one,
two, and three. This is to say that the results show a very strong correlation between citizens’
trust in their national government (H1), their perceived job insecurity (H2), and the receiving
of additional funds from the EU (H3) and the dependent variable of public trust in the EU.

 22