Media skepticism and reactions to political scandals: An analysis of the Trump

Abstract

While the discussion on the individual level variables that affect responses to political scandals has focused mainly on variables such as partisan identity or political cynicism, we suggest that media skepticism could also moderate whether and how individuals respond to political scandals. To test this relationship, we rely on panel data from the United States gathered before and after the Trump–Ukraine scandal occurred (Wave 1 in June 2019, Wave 2 in October 2019). Our results show that individuals who rank higher on media skepticism hold comparatively more positive views of Trump after the scandal, even when previous evaluations and alternative explanations are controlled for. Conversely, we find no effect of media skepticism in trust toward the US political system and government. We believe our findings have significant consequences to understanding the relationship between the governed and those governing in times of widespread media skepticism.

Keywords

Media skepticism scandals political evaluations selective exposure United States

Introduction

The effects of political scandals have long interested social scientists working from very different perspectives, which is hardly surprising, given their consequences can affect the functioning of democracies (von Sikorski, 2018). On the one hand, individuals may react negatively to political scandals, diminishing their support levels toward political institutions and actors. But, on the other hand, scandals may end up having positive consequences in terms of support, mainly when known to the public, and as long the politicians involved are punished for their misbehavior (Maier, 2010; Praino and Stockemer, 2021). While it seems uncontested to say that there is a high variation in how individuals react to political scandals, there is still room to understand the micro-foundations of this variation. This paper seeks to advance this literature by introducing media skepticism as an antecedent of reactions to political scandals. Building upon literature that examines how much information individuals receive about public affairs and how this information is processed (Garrett et al., 2012; Gil de Zúñiga et al., 2018), we expect high levels of media skepticism to diminish people’s negative reactions to political scandals. That is, higher levels of media skepticism will lead to less negative reactions in terms of political trust (buffering effect), after a scandal takes place.

To test this relationship, we use an online survey panel study conducted in the United States (US). The first wave of data collection began in June 2019, and the second one in October 2019, a couple of weeks after the Trump–Ukraine scandal made it to the front pages of influential media outlets. The scandal started with a whistleblower complaint filed on August 12th, 2019, in which an anonymous intelligence officer showed his concern because Trump may have used ‘the power of his office to solicit interference from a foreign country in the 2020 US elections’ (Mettler and Lieberman, 2020). This hint led to a phone call between Trump and the Ukrainian president, Volodymyr Zelensky, in which Trump used a rhetoric of ‘quid pro quo,’ alluding implicitly to withheld funding and inviting Zelensky to the White House. In exchange for that, Zelensky would announce investigations on the potentially corrupt behavior of the son of Joe Biden, Trump’s competitor for the 2020 elections, and allegations stating that Ukraine interfered in the 2016 US elections by hacking the Democratic National Committee’s network. Utilizing a quasi-experimental setting, our panel study allows us to observe changes in attitudes after a scandal while controlling for previous evaluations of actual political actors (i.e., Donald Trump) and institutions (i.e., US government and political system), something difficult to obtain when experiments with fictional candidates are applied (von Sikorski et al., 2020).

Our results show that media skepticism influences reactions to political scandals. Individuals who ranked higher on media skepticism displayed comparatively more favorable views of Trump after the Ukraine scandal, even when previous evaluations and relevant competing explanations were controlled for. The effect of media skepticism was not moderated by a key variable in this subfield, partisan identity, which speaks of the potential strength of our explanatory variable. We found no effects of media skepticism in trust towards the US political system or the government. We attributed this to the lack of short-term spillover effects in the case under examination. The implications of these results are detailed in the discussion and conclusion section, together with limitations of our study. An important one is that we cannot guarantee our results are solely explained by the Trump–Ukraine scandal, because we lack explicit questions about it in our panel survey. Therefore, while our results provide initial evidence for the buffering effect of media skepticism after scandals occur, more experimental studies will be necessary to confirm it.

Political scandals and media skepticism

While political scandals may occur whenever politicians transgress norms, the use of the term in social science research often includes the communication and information processes through which ‘alleged transgressions or failures of public figures, groups, organizations, or institutions are denounced with the aim of eliciting public outrage,’ also known as scandalization (Geiß, 2017: 1). This perspective emphasizes the joint existence of, first, an illegal/inappropriate behavior by a politician; second, media conglomerates that made it known to the public; and third, a public opinion that might change their opinion and even behavior. We derive from this approach that politicians’ behaviors susceptible to being ‘scandalized’ by media are not uncommon, although only a portion of them make it to the front page.

Research on the effects of political scandals on public opinion is organized along two main theoretical approaches: the dysfunctional and the functional one (Maier, 2010). The dysfunctional approach assumes that scandals are harmful to the image of both political institutions and actors. Its underlying idea is that individuals will react to the inappropriate or even illegal behavior from politicians with increased skepticism and distrust. Alternatively, the functional theory posits that reporting political scandals may have a positive effect on how political institutions are perceived. Far from suggesting that individuals reward political misconduct, what lies at the core of the functional theory is that citizens may end up being more trustful of the system if they perceive misconduct is identified and, essentially, punished. However, both theories agree in predicting that the image of the politicians involved in a scandal will be damaged (Maier, 2010; von Sikorski, 2018). Whether negative reactions spread beyond them, operationalized as spillover effect, is dependent on two intertwined factors: the extent to which individuals identify politicians involved in scandals as part of a larger network of political institutions, and the strength of these connections, dubbed as the accessibility–diagnosticity framework (Roehm and Tybout, 2006).

In line with the dysfunctional theory, empirical research has often found that when political scandals ocurr, overall political distrust increases and the image of the politicians is largely affected (Brody and Shapiro, 1989; Praino et al., 2013; Stockemer and Praino, 2019). Nonetheless, there are nuanced multilevel explanations for this phenomenon.

At the aggregate level, literature shows that scandals are likely to trigger more political distrust in situations of extreme economic uncertainty (i.e., with high inflation or unemployment issues), and whenever approval rates are low among supporters of opposition parties (Carlin et al., 2015; Nyhan, 2015). Attitudinal reactions to scandals are also dependent on how often they are reported in the media (coverage) and their treatment (framing) (Kepplinger et al., 2012; von Sikorski, 2018). Finally, at the individual level, the relationship seems mostly conditioned by partisan identity (Dancey, 2012; Wagner et al., 2012), but also by political cynicism and distrust (Dancey, 2012). In this regard, three main mechanisms have been identified that condition the outcomes of political scandals at the individual level (von Sikorski et al., 2020). First, scholars have consistently shown that individuals, by means of media selective exposure, look for information that is coherent with their beliefs and attitudes (Garrett, 2009). Second, individuals tend to practice selective perception and are likely to interpret that when exposed to media news, the information received is in agreement with their beliefs (Tsfati and Cappella, 2003). Third, motivated skepticism also drives this relationship, as individuals more easily assume arguments that are in line with their way of thinking while downplaying information that challenges it (Ditto and Lopez, 1992). The combination of these effects explains why partisan identity strongly moderates the outcomes of political scandals. Via selective exposure, individuals with a strong partisan identity are more likely to avoid media outlets and specific news that criticize the politicians/parties to which they feel attached (Stroud, 2010). Due to selective perception and motivated skepticism, these same individuals are more likely to maintain their perception of the politicians/parties involved in a scandal. This happens because even if they consume news about the scandal, they will be more prone to downplay attitude-challenging arguments or even to process these arguments in a way that makes them look in agreement with their beliefs (von Sikorski et al., 2020). This paper suggests similar underlining mechanisms explain how media skepticism shapes attitude change after a political scandal. To the best of our knowledge, this connection has not been considered yet, despite its potentially important implications in a context increasingly shaped by hostile perceptions of media.

Media skepticism reflects feelings of alienation and distrust towards mainstream media, which affects perceptions of credibility and reliability, and translates into lower levels of exposure (Tsfati, 2003). In the context of political scandals, we expect this variable to matter because of the crucial importance of media in making political scandals known to the public, which is well reflected in the ideas of ‘scandalization’ (Geiß, 2017) or ‘mediated scandals’ (Thompson, 2000). While political cynicism is likely to foster negative attitudinal reactions to political scandals (Dancey, 2012), we expect media skepticism to reduce them, for two main reasons. First, we expect that media skepticism, via selective exposure, will affect the overall amount of news to which individuals are exposed. Given that more exposure is associated with a higher likelihood of attitude change (Ernst et al., 2017), we should see that media skepticism buffers attitude change after a political scandal takes place, provided that mainstream actors mainly provide the information. Second, even if media skeptics are exposed to news about a scandal (Tsfati and Cappella, 2003), which is not unlikely given the complex informational environments citizens live in nowadays, the lack of credibility assigned to the source will increase the likelihood of selective perception and motivated skepticism, limiting too attitude change.

These two arguments lead to a common expectation: individuals with higher levels of media skepticism will change their political attitudes less after a political scandal occurs because they will be less likely to accept the ‘climate of opinion presented by the media’ (Tsfati, 2003: 69).

Building upon the results of the dysfunctional theory, we assume that political scandals will harm the evaluation of politicians involved and, to a lesser extent, in the assessment of political institutions (in this paper, US government and political system). Considering the effects of the theoretical framework exposed above, we expect the effect to vary due to media skepticism. Hence, we hypothesize that, after a scandal, individuals who rank higher on media skepticism will evaluate the politicians involved less negatively (H1a). Also, if attitudinal reactions spread beyond the politicians involved in the scandal (i.e., if spillover effects exist), we will see that media skepticism buffers negative evaluations towards political institutions (H1b). Furthermore, and given prior findings on the crucial association between political scandals and individuals’ partisanship, we also consider that the effect of media skepticism may be dependent on the latter. The combination of these two elements may trigger selective exposure, motivated skepticism, and selective perception in a way that makes the result greater than the sum of its parts. Therefore, we suggest that the buffering effect of media skepticism will be stronger for individuals that identify with the party involved in the scandal (H2a). If attitudinal reactions spread beyond the politicians involved in the scandal (i.e., if spillover effects exist), we will see a stronger buffering effect in the evaluations of political institutions among individuals who identify with the party involved in the scandal (H2b).

Our case study: The Trump–Ukraine scandal

The ‘Trump–Ukraine scandal’ started with a whistleblower complaint filed on August 12th, 2019. The whistleblower, an anonymous intelligence officer, showed his concern because Trump may have used ‘the power of his office to solicit interference from a foreign country in the 2020 U.S. election’ (Mettler and Lieberman, 2020). Subsequent information pointed to a phone conversation between Trump and the Ukrainian president, Volodymyr Zelensky. Shortly before this call, Trump had ordered the withholding of US$391 million in military and security aid to Ukraine. In his conversation with Zelensky, Trump used a ‘quid pro quo’ rhetoric, alluding implicitly to the withheld funding and inviting his equivalent to the White House. In exchange for that, Zelensky would announce investigations on two fronts: first, on the potentially corrupt behavior of the son of Joe Biden, Trump’s potential competitor for the 2020 elections; second, on allegations stating that Ukraine interfered in the 2016 US elections by hacking the Democratic National Committee’s network, opening the frame for Russia’s interference.

The Washington Post, a leading outlet in covering political scandals (Nyhan, 2015), played a key role in making this situation known to public opinion. Its editorial board first reported the situation on September 5th, 2019, and by September 19th the diary published the whistleblower complaint on Trump’s communications with a (still unknown) foreign leader (Nakashima, 2019). This event led to President Trump posting several statements on Twitter accusing the whistleblower of being ‘partisan’ and calling the Washington Post ‘Fake News Media.’ The Washington Post kept reporting about the scandal on its pages, which subsequently influenced the agenda of other media outlets (Pramuk, 2019; The New York Times, 2019; The Washington Post, 2019; Wolf, 2019). Although different framings appeared that put the emphasis on distinct actors involved in the process (Blitzer, 2021; Dilanian and Winter, 2020), the importance of the scandal and the attention it received is beyond doubt. It was covered by virtually all relevant media in the country, even more since Trump kept accusing Biden of corruption after the revealing of the phone call, which led to an impeachment inquiry opened by House Speaker Nancy Pelosi (Trump was finally impeached by the House of Representatives on December 18th, under accusations of abuse of power and the obstruction of Congress), and it affected public opinion of Trump about this impeachment process, especially among Democrats and independents (McCarthy 2019). The question is, how did media skepticism, alone and in combination with partisan identity, influence individuals’ responses to the scandal?

Methods

Data for this research comes from an online panel survey conducted in the United States in two waves. The first wave (W1) of the collection started in June 2019 (N = 1,338), and the second one (W2) in October 2019 (N = 511), a few weeks after the Trump–Ukraine scandal was made known to the public (a comparison of aggregated socio-demographic features in the two waves is in the online appendix, Table OA.1). The principal investigator at the MiLab Research Unit hired IPSOS Austria to provide respondents for the survey, with the questionnaires administered via Qualtrics at the University of Vienna. IPSOS maintains and curates a massive panel of hundreds of thousands of subjects from where respondents were selected from a stratified and randomized subsample of 3000 individuals, so they reflect key demographic elements from the US census (i.e., education, gender, and income) (Gil de Zúñiga et al., 2021). Although acknowledging the limitations of non-probabilistic sampling, this technique allows us to obtain a diverse and ‘census-balanced sample’ appropriate for our research interest. This is particularly so as we do not focus on estimating population values, but we rather develop multivariate models to assess the initial relationship between two main survey variables: media skepticism and political evaluations (Baker et al., 2010). The questionnaire we used contained an extensive battery of items designed to measure different types of political and media-related attitudes and patterns of media consumption. All indexes, otherwise stated, were measured on a 1–10 Likert type scale.

Dependent variables (DVs)

To see the effects of the scandal, we separately used three main questions that tap into evaluations of, first, the political system of the United States: ‘Please rate your feelings of trust towards the political system of the U.S.’ (W1 M = 3.96, SD = 2.52; W2 M = 3.77, SD = 2.41); second, the government: ‘Please rate your feelings of trust towards the government’ (W1 M = 4.39, SD = 2.47; W2 M = 4.37, SD = 2.46); and third, US president, Donald Trump: ‘We would like to know your feelings toward Donald Trump,’ on a scale from 0 to 10, in which 0 means very unfavorable, and 10 very favorable (W1 M = 5.06, SD = 3.9; W2 M = 4.89, SD = 4.06).

Independent variables (IVs)

To measure media skepticism, we used the averaged index of three questions: ‘I think the news media prioritize being first to report a story’; ‘I think the news media get in the way of society solving its problems’; ‘Overall, I am skeptical about the news media’ (W1 Cronbach’s α = .80, M = 6.58, SD = 2.25) (see Tsfati, 2003).¹ Regarding partisan identity, we utilized a question that asked respondents where they place themselves on a 0–10 scale where the extremes represent strong Democrat and strong Republican, respectively, and middle positions self-location as independent. From it, we created three categories: Democrat/Democrat-leaning (0–4), independent (5), and Republican/Republican leaning (6–10) (W1 = 478 Republican/Republican leaning, 443 Democrat/Democrat leaning, 363 independent). An alternative operationalization that considers a broader category of independents (4–6) does not affect our results.

Rest of covariates and controls

To isolate the effect of the scandal on attitudes as much as possible, we incorporated an exhaustive battery of controls that allowed for considering alternative explanations. We controlled for levels of generalized trust using the average of two questions: ‘Generally speaking, would you say that most people can be trusted, or that you need to be very careful?’; ‘Could you tell me how much you trust people that you meet for the first time?’ (Spearman-Brown ρ = .84, M = 4.18, SD = 2.35); satisfaction with life: ‘In most ways, my life is close to my ideal’; ‘All things considered, I am satisfied with my life as a whole’ (Spearman-Brown ρ = .87, M = 6.04, SD = 2.38); dissatisfaction with the government in fields not related to the scandal, such as ‘crime, unemployment, difference between rich and poor, and the cost of living’ (Cronbach’s α = .78, M = 6.82, SD = 2.04), and media consumption, a composite index of respondents’ usage of newspapers, radio, TV, social media, and online platforms to get news.² This index relates to 41 questions in which respondents answered questions about the frequency with which they get news from different media outlets (Cronbach’s α = .95, M = 3.92, SD = 1.76).³ We further controlled for age, gender (female as reference), education (Bachelor’s degree or more as reference), race (white as reference), and income levels (dichotomous variable considering the median family income in the United States).⁴

Admittedly, the availability of specific questions related to the scandal would have been ideal to pinpoint its effects on political attitudes, but, as it is often the case in quantitative studies of political scandals, data were not originally collected for these purposes (Geiß, 2017). In this sense, we were lucky to capture the occurrence of an exogenous shock (the Trump–Ukraine scandal) between the first and second wave of our longitudinal study, which situates our research within the frame of ‘natural experiments’ combined with survey research (Barabas and Jerit, 2010; Minkus et al., 2019). However, one must consider the two main strengths of our design. First, our study evaluates actual candidates and political institutions, which reduces possible biases associated with motivated reasoning in experimental designs with fictional candidates (von Sikorski et al., 2020). Second, due to its panel nature, we have data on the same individuals before and after the external natural ‘stimuli’ (i.e., the Trump–Ukraine scandal) affected the political scene.

Analytical approach

To analyze the relationship between media skepticism, alone and in combination with partisan identity, and political evaluations after a scandal, we use Ordinary Least Square Regression (OLS). We conduct three different models: a cross-sectional one where all variables used to belong to our baseline survey in the first wave (DV and IVs from W1); a lagged one, which addresses some temporality relationships between wave 1 and wave 2 (DV from W2, all IVs from W1); and finally, an autoregressive model, which allows for more stringent causal order effects in time, as it also controls for prior levels of the dependent variable in time 1 (lagged model plus a control of evaluations of political institutions and Trump from W1). While the first two models allow for a control of the consistency and coherence of our results, we focus our interpretation on the third and last model, the autoregressive. This model allows us to specifically pay attention to the association between media skepticism and attitude change after the scandal.⁵

Results

A preliminary analysis of descriptive data shows that individuals displayed more negative evaluations of the US political system, government, and Donald Trump after the scandal (comparing data from W1 and W2). On aggregate terms, individuals trusted less the U.S political systems and the government, but a different pattern emerged from the question that measures support for Trump. Overall, respondents showed less favorable feelings towards Trump, but this happened even if individuals moved towards both extremes (extremely favorable and unfavorable) (Table 1). The extent to which changes in evaluations can be attributed to the Trump–Ukraine scandal is easier to observe at the individual level, where we can control both for previous evaluations and alternative explanations with an exhaustive battery of controls. Strictly controlling for remaining sources of variation is key to sustain that the observed effects are due to the scandal, since we do not have specific questions about it.

Table 1.

Average evaluations of political institutions/actors.

Variable (min–max)	Wave 1	Wave 2
Variable (min–max)	Mean (SD)	Mean (SD)
US political system (1–10)	3.96 (2.52)	3.77 (2.41)
Government (1–10)	4.39 (2.47)	4.37 (2.46)
Donald Trump (0–10)	5.06 (3.9)	4.89 (4.06)

Our cross-sectional and lagged models show a consistent relationship between media skepticism and political evaluations (Tables 2 and 3). Individuals who rank higher on media skepticism display lower trust toward the US political system and the government and more favorable views of Donald Trump. The connection between media skepticism and trust in institutions taps well into the relationship between media and political trust. The coefficient in the evaluations of Trump was expected attending to his discourse toward mainstream media agencies (Lischka, 2019). However, this data cannot shed light on the relationship between media skepticism and attitudes after the scandal, for which we rely on our autoregressive model. In the autoregressive model we find that, unsurprisingly, political evaluations in the first wave are the best predictor of political evaluations in the second wave (Table 4). Still, higher levels of media skepticism significantly relate to more favorable views of Trump after the scandal took place (see also online appendix, Table OA.2). However, the effect of media skepticism is not significant for trust towards the political system and the government. We see a consistent effect of identifying as independent on the partisan scale among the controls included. As compared to Republicans (our reference category), independents show more negative evaluations in the three models, which may correlate with independents having a not so strong apriorist opinion on politicians and institutions that makes them more likely to react to scandals.⁶ Democrats rank lower than Republicans in their evaluations of Trump after the scandal, even when previous evaluations are accounted for, which is in agreement with previous findings (von Sikorski et al., 2020). Other controls have no robust effect on the evaluations of the political system, the government, and Trump.⁷

Table 2.

Cross-sectional model. Evaluations of US political system, government, and Trump.

Predictors	Dependent variable
Predictors	US political system (Wave 1)	Government (Wave 1)	Trump (Wave 1)
Gender (female as reference)	−0.017 (0.127)	−0.233* (0.130)	−0.399** (0.181)
Age	−0.202** (0.081)	0.020 (0.083)	0.152 (0.116)
Education	−0.043 (0.142)	0.164 (0.145)	−0.451** (0.202)
Income	−0.324** (0.144)	−0.085 (0.147)	−0.538*** (0.206)
Race (White as reference)	−0.262* (0.157)	−0.182 (0.160)	0.339 (0.224)
Satisfaction with life	0.078*** (0.029)	0.117*** (0.030)	0.129*** (0.042)
Trust towards people	0.333*** (0.030)	0.311*** (0.030)	−0.056 (0.043)
Dissatisfaction gov. policies	−0.060* (0.035)	−0.012 (0.036)	−0.236*** (0.050)
News consumption	0.476*** (0.043)	0.382*** (0.044)	0.127** (0.062)
Democrat	−0.346** (0.160)	−0.282* (0.164)	−4.904*** (0.229)
Independent	−0.312* (0.160)	−0.259 (0.164)	−2.855*** (0.229)
Media skepticism	−0.125*** (0.031)	−0.157*** (0.032)	0.295*** (0.044)
Constant	2.475*** (0.445)	2.410*** (0.454)	6.591*** (0.637)
Observations	1,067	1,071	1,068
R²	0.337	0.285	0.463
Adjusted R²	0.329	0.277	0.457
Residual std. error	1.999 (df = 1054)	2.045 (df = 1058)	2.854 (df = 1055)
F statistic	44.590*** (df = 12; 1054)	35.122*** (df = 12; 1058)	75.713*** (df = 12; 1055)

Estimates are coefficients (ordinary least squares regression) with standard errors in parentheses.

p < 0.10. **p < 0.05. ***p < 0.01.

Table 3.

Lagged model. Evaluations of US political system, government, and Trump.

Predictors	Dependent variable
Predictors	US political system (Wave 2)	Government (Wave 2)	Trump (Wave 2)
Gender (female as reference)	−0.348* (0.210)	−0.475** (0.222)	−0.424 (0.297)
Age	−0.314** (0.149)	0.003 (0.157)	−0.156 (0.211)
Education	0.046 (0.222)	0.346 (0.235)	−0.526* (0.315)
Income	−0.547** (0.233)	−0.284 (0.247)	−0.381 (0.332)
Race (White as reference)	0.020 (0.273)	0.411 (0.290)	0.188 (0.384)
Satisfaction with life	0.050 (0.046)	0.120** (0.049)	0.177*** (0.066)
Trust towards people	0.209*** (0.051)	0.152*** (0.054)	0.004 (0.072)
Dissatisfaction gov. policies	−0.127** (0.059)	0.003 (0.062)	−0.292*** (0.082)
News consumption	0.350*** (0.075)	0.391*** (0.079)	−0.076 (0.105)
Democrat	−0.260 (0.271)	−0.396 (0.286)	−4.978*** (0.382)
Independent	−0.648** (0.263)	−0.777*** (0.278)	−3.155*** (0.372)
Media skepticism	−0.095* (0.050)	−0.202*** (0.053)	0.403*** (0.072)
Constant	4.609*** (0.810)	3.460*** (0.857)	7.511*** (1.145)
Observations	432	431	418
R²	0.199	0.189	0.505
Adjusted R²	0.176	0.165	0.490
Residual std. error	2.055 (df = 419)	2.171 (df = 418)	2.854 (df = 405)
F statistic	8.689*** (df = 12; 419)	8.106*** (df = 12; 418)	34.413*** (df = 12; 405)

Estimates are coefficients (ordinary least squares regression) with standard errors in parentheses.

p < 0.10. **p < 0.05. ***p < 0.01.

Table 4.

Autoregressive model. Evaluations of US political system, government, and Trump.

Predictors	Dependent variable
Predictors	US political system (Wave 2)	Government (Wave 2)	Trump (Wave 2)
US political system (W1)	0.555*** (0.042)
Government (W1)		0.660*** (0.041)
Trump (W1)			0.878*** (0.026)
Gender (female)	−0.332* (0.177)	−0.349** (0.175)	−0.016 (0.150)
Age	−0.074 (0.126)	0.110 (0.124)	−0.126 (0.106)
Education	0.024 (0.187)	0.221 (0.185)	−0.200 (0.159)
Income	−0.244 (0.197)	−0.083 (0.194)	−0.243 (0.167)
Race (White)	0.138 (0.230)	0.343 (0.228)	0.203 (0.194)
Satisfaction with life	−0.018 (0.039)	0.018 (0.039)	0.031 (0.033)
Trust towards people	0.018 (0.045)	−0.056 (0.044)	−0.011 (0.036)
Dissatisfaction gov. policies	−0.101** (0.049)	−0.023 (0.049)	−0.094** (0.042)
News consumption	0.162** (0.064)	0.211*** (0.063)	−0.035 (0.053)
Democrat	−0.012 (0.229)	−0.062 (0.226)	−0.492** (0.232)
Independent	−0.400* (0.223)	−0.368* (0.220)	−0.351* (0.205)
Media skepticism	−0.018 (0.043)	−0.069 (0.043)	0.091** (0.037)
Constant	2.663*** (0.700)	1.476** (0.684)	1.458** (0.604)
Observations	430	431	418
R²	0.437	0.500	0.874
Adjusted R²	0.419	0.484	0.870
Residual std. error	1.728 (df = 416)	1.707 (df = 417)	1.440 (df = 404)
F statistic	24.796*** (df = 13; 416)	32.076*** (df = 13; 417)	216.101*** (df = 13; 404)

Estimates are coefficients (ordinary least squares regression) with standard errors in parentheses.

p < 0.10. **p < 0.05. ***p < 0.01.

While we see the effect of media skepticism moderating reactions towards the politician involved in the scandal (supporting H1a), we find no effect of media skepticism on changing evaluations towards political institutions (against H1b). However, the existence of a gap in the perception of Trump as a function of media skepticism, even when previous attitudes are controlled for, can have two main different interpretations. First, the gap may appear via the buffering effect of media skepticism concerning attitude change (i.e., attitudes are overall more negative after the scandal, which is more transparent for individuals who display lower levels of skepticism towards media). Second, the gap may present because individuals who are highly skeptical of media, far from reacting negatively to the scandal, see Trump in a more positive light after he is ‘attacked’ by the mainstream media they strongly distrust.

To test which of these mechanisms was more prevalent, we first used the cross-sectional model to predict attitudes towards Trump for individuals at maximum and minimum levels of media skepticism (predicted attitudes were 5.98 and 8.94, respectively, z = −5.02, p < .000, two-tailed).⁸ In a second step, we used the autoregressive model to predict attitudes towards Trump for individuals displaying maximum and minimum levels of media skepticism who had the average predicted attitudes in the first wave. New predicted values were 5.15 and 9.19, respectively (z = −5.95, p < .000, two-tailed), which suggests the existence of a polarization effect taking place at the extreme values of media skepticism (i.e., while individuals ranking very low on media skepticism worsened their perception of Trump after the scandal, individuals who were highly skeptical of media even improved their perception slightly). The polarization effect, however, disappeared as more moderate values of media skepticism were taken as reference. For example, attitudes towards Trump did not improve among individuals who ranked 7 or 8 on the scale of media skepticism, supporting the buffering effect explanation among larger sectors of the population.⁹

To test the combined effect of media skepticism and partisan identity, we ran an additional model that included an interaction term between these two variables. The interaction term was not significant, suggesting the effect of media skepticism on political evaluations after a scandal did not vary across categories of partisan identity (Table 5). A graphical representation presented in the online appendix (Figure OA.3) shows that slopes for predicted results run largely parallel and confidence intervals overlap consistently, further supporting this claim. This does not mean that partisan identity was irrelevant to explain trust towards political institutions or, even more importantly, specific political actors. While the slopes were not significantly different, intercepts varied as a function of partisan identity (in all three models for independents, in favorable perceptions of Trump for Democrats too). The effect of the individual terms existed but, recurring to our reasoning above, the final effect responded to the sum of its parts (partisan identity and media skepticism, with no moderating effect). Thus, we found no evidence to support H2a and H2b.¹⁰

Table 5.

Autoregressive model with interactions.

Predictors	Dependent variable
Predictors	US political system (Wave 2)	Government (Wave 2)	Trump (Wave 2)
US political system (W1)	0.559*** (0.042)
Government (W1)		0.662*** (0.041)
Trump (W1)			0.877*** (0.026)
Gender (female as reference)	−0.315* (0.177)	−0.337* (0.175)	−0.011 (0.150)
Age	−0.079 (0.126)	0.106 (0.124)	−0.126 (0.106)
Education	0.016 (0.187)	0.219 (0.185)	−0.199 (0.159)
Income	−0.254 (0.197)	−0.093 (0.195)	−0.250 (0.168)
Race (White as reference)	0.129 (0.230)	0.340 (0.229)	0.201 (0.194)
Satisfaction with life	−0.016 (0.039)	0.021 (0.039)	0.034 (0.034)
Trust towards people	0.017 (0.045)	−0.059 (0.044)	−0.013 (0.036)
Dissatisfaction gov. policies	−0.106** (0.050)	−0.025 (0.049)	−0.094** (0.042)
News consumption	0.162** (0.065)	0.214*** (0.063)	−0.030 (0.053)
Democrat	0.406 (0.694)	0.566 (0.686)	0.106 (0.590)
Independent	−0.910 (0.747)	−0.456 (0.740)	−0.130 (0.631)
Media skepticism	−0.014 (0.070)	−0.038 (0.070)	0.133** (0.061)
Democrat × media skepticism	−0.071 (0.097)	−0.098 (0.095)	−0.092 (0.082)
Independent × media skepticism	0.081 (0.102)	0.020 (0.100)	−0.027 (0.086)
Constant	2.663*** (0.855)	1.233 (0.844)	1.122 (0.723)
Observations	430	431	418
R²	0.440	0.502	0.875
Adjusted R²	0.420	0.484	0.870
Residual std. error	1.727 (df = 414)	1.707 (df = 415)	1.441 (df = 402)
F statistic	21.668*** (df = 15; 414)	27.902*** (df = 15; 415)	187.076*** (df = 15; 402)

Estimates are coefficients (ordinary least squares regression) with standard errors in parentheses.

p < 0.10 **p < 0.05 ***p < 0.01.

Discussion and conclusion

This study sought to clarify the type of individual level antecedents that influence the effects of political scandals over political elected officials and institutions. In doing that, we aimed to understand better how the governed perceive political misbehavior and react to it, which has important implications for the stability of governments and the overall perception of the political system. Here, we focused on the relationship between media skepticism and attitude change after a political scandal.

Our theoretical expectation was that individuals who rank higher on media skepticism would be less likely to be exposed to (mainstream) media news and less likely to accept their arguments. This would affect, in turn, their reaction to political scandals. Our results supported this theoretical proposition. According to our empirical evidence, individuals who ranked higher on media skepticism displayed more favorable views of Trump after the Ukraine scandal, even when previous evaluations of Trump were controlled for. This effect remained after controlling for important predictors of political evaluations and different patterns of news consumption and it seemed explained by a combination of buffering and backfire effects, with a clear predominance of the former (the latter was only visible when the highest possible levels of media skepticism were considered).

While we found no significant contribution of media skepticism on changing evaluations towards the US political system or the government, we think this can demonstrate a general lack of short-term spillover effects derived from the scandal. In this vein, and provided that the effects of scandals go beyond the political officials involved, we would expect a similar effect of media skepticism on support for political institutions. While our results for media skepticism focus on the evaluation of the politician initially splashed in the political scandal, our argument could be applied to the evaluation of political institutions whenever accessibility–diagnosticity mechanisms favor the appearance of spillover effects (Roehm and Tybout, 2006). Overall, we speculate the lack of spillover effects could be influenced by the strong personal implication of Trump in the scandal, the fatigue effects derived from the exposure to a series of misbehaviors from the president (Collinson, 2019a; Kumlin and Esaiasson, 2012), and/or the short time passed between the scandal becoming known and our survey being fielded. However, further studies should specifically expand our study to test these alternative ad hoc theoretical explanations. These would be of particular importance to unravel the associations between media skepticism and overall political trust, mainly when new technologies and social media are candidates to increase the prevalence of media skepticism (Cozzens and Contractor, 1987).

Albeit the findings presented help clarify the connection between media skepticism, political trust, and the effects of political scandals, the study is not immune to limitation. First, we rely on a quasi-natural experimental condition and online panel survey data. Although this has important methodological advantages regarding controlling for previous levels of trust towards actual politicians and institutions, further studies based on sole experimental conditions may further help to shed light on the relationship between media skepticism, political scandals, and political evaluations from citizens. Particularly important in this regard is that we cannot guarantee our results are solely explained by the Trump–Ukraine scandal, even if this was certainly a major issue around his person (as shown above), because we lack explicit questions about it. Our strategy has focused on considering most relevant predictors of political evaluations together with alternative explanations for attitudinal changes, but we must recognize Donald Trump’s presidency was well known for different controversies of varying intensity that may have also affected public assessments of his figure.¹¹ Overall, we are far from claiming to have the final word on the extent to which media skepticism buffers reactions to political scandals. Nevertheless, we believe our design will contribute to this discussion by complementing experimental approaches that are better equipped to identify causality but struggle more with replicating actual political conditions.

Second, we are focusing our analysis on a particular scandal in the United States. This posits advantages in terms of controlling for potential confounders in the relationship under study. Still, more comparative studies will be necessary to know whether media skepticism moderates reactions to political scandals beyond the United States and Trump’s presidency. We believe two main aspects need acknowledgment before extrapolating our results to other cases: first, the particular relation of Donald Trump with mainstream media (Grynbaum, 2017), including the fact that Trump himself may have fueled media skepticism with his discourses (Meeks 2019); second, the fact that the scandal under consideration in our research involves political figures of the highest level (both Trump and Biden), which could make it more likely that citizens will become interested in it. We speculate these factors may indeed affect the overall aggregated reaction to the scandal due to the number of people exposed to it combined with the prevalence of media skeptics, but the individual association between media skepticism and attitudinal reaction should not be determined by them. However, only future studies can determine empirically if our theoretical link between media skepticism and reaction to political scandals holds in different settings that are less shaped by media skepticism and involve lesser-known political figures.

The results of our research have implications for our understanding of whether and how political scandals influence public opinion. However, they also evidence significant practical challenges that transcend academic discussions. Empirical data show that distrust towards media has taken an unprecedented magnitude (Dahlgren, 2018). This can be related to gaps between expectations and outcomes received from media and further connected to the increasing number of individuals highly involved in controversial topics who perceived the media as biased (Engelke et al., 2019). It goes without saying that healthy democratic societies display critical attitudes also towards media, and some manipulative behaviors from media indeed deserve critical judgments (van Dijk, 2017). However, extended skepticism towards media can challenge some of the functions traditionally assigned to them, such as informing and promoting public debates. Although we are hardly the first one to refer to this trend, we show empirically that media skepticism affects responses to political scandals, which in turn may also influence mechanisms of accountability through voting decisions and, relatedly, to overall levels of political trust.

Supplemental Material

sj-docx-1-ips-10.1177_01925121211073005 – Supplemental material for Media skepticism and reactions to political scandals: An analysis of the Trump–Ukraine case

Supplemental material, sj-docx-1-ips-10.1177_01925121211073005 for Media skepticism and reactions to political scandals: An analysis of the Trump–Ukraine case by Hugo Marcos-Marne, Pablo González-González and Homero Gil de Zúñiga in International Political Science Review

Supplemental Material

sj-R-2-ips-10.1177_01925121211073005 – Supplemental material for Media skepticism and reactions to political scandals: An analysis of the Trump–Ukraine case

Supplemental material, sj-R-2-ips-10.1177_01925121211073005 for Media skepticism and reactions to political scandals: An analysis of the Trump–Ukraine case by Hugo Marcos-Marne, Pablo González-González and Homero Gil de Zúñiga in International Political Science Review

Footnotes

Acknowledgements

The authors would like to thank three anonymous reviewers for their constructive comments, which helped us to improve the manuscript.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Late stages of this work at the Democracy Research Unit (DRU) have benefited from the support of the Spanish National Research Agency’s Program for the Generation of Knowledge and the Scientific and Technological Strengthening Research + Development Grant PID2020-115562GB-I00. The last author is funded by the ‘Beatriz Galindo Program’ from the Spanish Ministry of Science, Innovation & Universities, and the Junta de Castilla y León.

ORCID iDs

Hugo Marcos-Marne

Pablo González-González

Homero Gil de Zúñiga

Supplemental material

Supplemental material for this article is available online.

Notes

Author biographies

Hugo Marcos-Marne is an Assistant Professor at the University of Salamanca, and member of the Democracy Research Unit (DRU) at the same institution. His research focuses on public opinion, electoral behavior, populism, and national identities.

Pablo González-González is a doctoral student in Political Science at the University of Salamanca, and a member of the Democracy Research Unit (DRU). His research interests revolve around quantitative methods applied to political communication, social media, extremism, and political behavior.

Homero Gil de Zuñiga currently serves as Distinguished Research Professor at University of Salamanca, where he directs the Democracy Research Unit (DRU). He is also a Professor at Pennsylvania State University, and Senior Research Fellow at Universidad Diego Portales, Chile. Overall, the work that takes place at the DRU deals with the development of theoretically driven research, contributing to shed a social scientific light over social media and new technologies effects in the arena of Political Communication.

References

Baker

Reg

Blumberg

Stephen J.

Brick

J. Michael

Couper

Mick P.

Courtright

Melanie

Dennis

J. Michael

Dillman

Don

Frankel

Martin R.

Garland

Philip

Groves

Robert M

Kennedy

Courtney

Krosnick

Jon

Lavrakas

Paul J

(2010) Research Synthesis: AAPOR report on online panels. Public Opinion Quarterly 74(4): 711–781. Available at: https://www-jstor-org.web.bisu.edu.cn/stable/40927166

Barabas

Jason

Jerit

Jennifer

(2010) Are Survey Experiments Externally Valid? American Political Science Review 104(2): 226–242. DOI: 10.1017/S0003055410000092.

Blitzer

Ronn

(2021) Ukraine’s Zelensky ‘Offended’ by Media Reporting That Trump ‘Put Pressure’ on him. Fox News. Available at: https://www.foxnews.com/politics/ukraine-zelensky-offended-trump-phone-call-pressure (accessed 18 February 2021).

Brody

Richard A

Shapiro

Catherine R

(1989) Policy Failure and Public Support: The Iran-contra affair and public assessment of President Reagan. Political Behavior 11(4): 353–369. Available at: https://www-jstor-org.web.bisu.edu.cn/stable/586163

Carlin

Ryan E

Love

Gregory J

Martínez-Gallardo

Cecilia

(2015) Cushioning the Fall: Scandals, economic conditions, and executive approval. Political Behavior 37(1): 109–130. DOI: 10.1007/s11109-014-9267-3.

Collinson

Stephen

(2019a) It’s Nearly Impossible to Track All the Scandals Swirling Around Trump. CNN. Available at: https://edition.cnn.com/2019/09/10/politics/donald-trump-scandals/index.html

Collinson

Stephen

(2019b) Trump’s Controversies Show his Presidency is Really All About himself. CNN. Available at: https://edition.cnn.com/2019/09/09/politics/donald-trump-politics-alabama-hurricane-afghanistan-business/index.html

Cozzens

Michael D

Contractor

Noshir S

(1987) The Effect of Conflicting Information on Media Skepticism. Communication Research 14(4): 437–451. DOI: 10.1177/009365087014004004.

Dahlgren

Peter

(2018) Media, Knowledge and Trust: The deepening epistemic crisis of democracy. Javnost - The Public 25(1–2): 20–27. DOI: 10.1080/13183222.2018.1418819.

10.

Dancey

Logan

(2012) The Consequences of Political Cynicism: How cynicism shapes citizens’ reactions to political scandals. Political Behavior 34(3): 411–423. DOI: 10.1007/s11109-011-9163-z.

11.

Dilanian

Ken

Winter

Tom

(2020) Here’s What Happened When NBC News Tried to Report on the Alleged Hunter Biden Emails. NBC News. Available at: https://www.nbcnews.com/politics/2020-election/here-s-what-happened-when-nbc-news-tried-report-alleged-n1245533 (accessed 18 February 2021).

12.

Ditto

Peter H

Lopez

David F

(1992) Motivated Skepticism: Use of differential decision criteria for preferred and nonpreferred conclusions. Journal of Personality and Social Psychology 63(4): 568–584.

13.

Engelke

Katherine M

Hase

Valerie

Wintterlin

Florian

(2019) On Measuring Trust and Distrust in Journalism: Reflection of the status quo and suggestions for the road ahead. Journal of Trust Research 9(1): 66–86. DOI: 10.1080/21515581.2019.1588741.

14.

Ernst

Nicole

Kühne

Rinaldo

Wirth

Werner

(2017) Effects of Message Repetition and Negativity on Credibility Judgments and Political Attitudes. International Journal of Communication 11: 3265–3285.

15.

Garrett

R Kelly

(2009) Politically Motivated Reinforcement Seeking: Reframing the selective exposure debate. Journal of Communication 59(4): 676–699. DOI: 10.1111/j.1460-2466.2009.01452.x.

16.

Garrett

R Kelly

Bimber

Bruce

de Zuniga

Homero Gil

Heinderyckx

François

Kelly

John

Smith

Marc

(2012) Transnational Connections| New ICTs and the Study of Political Communication. International Journal of Communication 6: 18. Available at: https://ijoc.org/index.php/ijoc/article/view/1112 (accessed 16 December 2021).

17.

Geiß

Stefan

(2017) Scandalization. In The International Encyclopedia of Media Effects. Wiley, 1–11. Available at: https://onlinelibrary-wiley-com-443.web.bisu.edu.cn/doi/abs/10.1002/9781118783764.wbieme0198 (accessed 18 February 2021).

18.

Gil de Zúñiga

Homero

Huber

Brigitte

Strauß

Nadine

(2018) Social Media and Democracy. El Profesional de la Información 27(6): 1172. Available at: https://revista.profesionaldelainformacion.com/index.php/EPI/article/view/epi.2018.nov.01 (accessed 18 May 2021).

19.

Gil de Zúñiga

Homero

González-González

Pablo

Goyanes

Manuel

(2021) Pathways to Political Persuasion: Linking online, social media, and fake news with political attitude change through political discussion. American Behavioral Scientist.

20.

Grynbaum

Michael

(2017) Trump Strategist Stephen Bannon Says Media Should ‘Keep Its Mouth Shut.’ The New York Times. Available at: https://www.nytimes.com/2017/01/26/business/media/stephen-bannon-trump-news-media.html

21.

Kepplinger

Hans Mathias

Geiss

Stefan

Siebert

Sandra

(2012) Framing Scandals: Cognitive and emotional media effects. Journal of Communication 62(4): 659–681. DOI: 10.1111/j.1460-2466.2012.01653.x.

22.

Kumlin

Staffan

Esaiasson

Peter

(2012) Scandal Fatigue? Scandal elections and satisfaction with democracy in Western Europe, 1977–2007. British Journal of Political Science 42(2): 263–282. DOI: 10.1017/S000712341100024X.

23.

Lischka

Juliane A

(2019) A Badge of Honor? Journalism Studies 20(2): 287–304. DOI: 10.1080/1461670X.2017.1375385.

24.

McCarthy

Tom

(2019) Support for Impeachment Surges Amid Trump–Ukraine Scandal | Donald Trump. The Guardian. Available at: https://www.theguardian.com/us-news/2019/sep/30/impeachment-support-poll-trump-ukraine (accessed 18 February 2021).

25.

Maier

Jürgen

(2010) The Impact of Political Scandals on Political Support: An experimental test of two theories. International Political Science Review 32(3): 283–302. DOI: 10.1177/0192512110378056.

26.

Meeks

Lindsey

(2019) Defining the Enemy: How Donald Trump frames the news media. Journalism & Mass Communication Quarterly 97(1): 211–234. Available at: https://journals-sagepub-com-s.web.bisu.edu.cn/doi/full/10.1177/1077699019857676 (accessed 23 September 2021).

27.

Mettler

Suzanne

Lieberman

Robert C.

(2020) Four Threats: The Recurring Crises of American Democracy. New York: St. Martin’s Press.

28.

Minkus

Lara

Deutschmann

Emanuel

Delhey

Jan

(2019) A Trump Effect on the EU’s Popularity? The U.S. presidential election as a natural experiment. Perspectives on Politics 17(2): 399–416. DOI: 10.1017/S1537592718003262.

29.

Nakashima

Ellen

(2019) Whistleblower Complaint About President Trump Involves Ukraine, According to Two People Familiar With the Matter. Available at: https://www.washingtonpost.com/national-security/whistleblower-complaint-about-president-trump-involves-ukraine-according-to-two-people-familiar-with-the-matter/2019/09/19/07e33f0a-daf6-11e9-bfb1-849887369476_story.html

30.

Nyhan

Brendan

(2015) Scandal Potential: How political context and news congestion affect the president’s vulnerability to media scandal. British Journal of Political Science 45(2): 435–466. DOI: 10.1017/S0007123413000458.

31.

Praino

Rodrigo

Stockemer

Daniel

(2021) The Electoral Consequences of Scandals: A meta-analysis. Parliamentary Affairs. Available at: https://academic-oup-com-s.web.bisu.edu.cn/pa/advance-article/doi/10.1093/pa/gsaa068/6299982 (accessed 24 September 2021).

32.

Praino

Rodrigo

Stockemer

Daniel

Moscardelli

Vincent G

(2013) The Lingering Effect of Scandals in Congressional Elections: Incumbents, challengers, and voters. Social Science Quarterly 94(4): 1045–1061. DOI: 10.1111/ssqu.12046.

33.

Pramuk

Jacob

(2019) Whistleblower complaint is out: It alleges Trump abused power to influence 2020 election. Available at: https://www.cnbc.com/2019/09/26/house-intelligence-committee-releases-whistleblower-complaint-about-trump.html

34.

Roehm

Michelle L

Tybout

Alice M

(2006) When Will a Brand Scandal Spill Over, and How Should Competitors Respond? Journal of Marketing Research 43(3): 366–373. DOI: 10.1509/jmkr.43.3.366.

35.

Stockemer

Daniel

Praino

Rodrigo

(2019) The Good, the Bad and the Ugly: Do attractive politicians get a ‘break’ when they are involved in scandals? Political Behavior 41(3): 747–767. DOI: 10.1007/s11109-018-9469-1.

36.

Stroud

Natalie Jomini

(2010) Polarization and Partisan Selective Exposure. Journal of Communication 60(3): 556–576. DOI: 10.1111/j.1460-2466.2010.01497.x.

37.

The New York Times (2019) Trump’s Call With the Ukrainian President. Available at: https://www.nytimes.com/interactive/2019/09/25/us/politics/trump-ukraine-transcript.html

38.

The Washington Post (2019) The Washington Post Announces Plans to Expand its Investigative Journalism. Available at: https://www.washingtonpost.com/pr/2019/06/20/washington-post-announces-plans-expand-its-investigative-journalism/

39.

Thompson

John

(2000) Political Scandal: Power and Visibility in the Media Age. Cambridge: Cambridge Polity Press.

40.

Tsfati

Yariv

(2003) Media Skepticism and Climate of Opinion Perception. International Journal of Public Opinion Research 15(1): 65–82. Available at: https://academic-oup-com-s.web.bisu.edu.cn/ijpor/article-lookup/doi/10.1093/ijpor/15.1.65 (accessed 19 February 2021).

41.

Tsfati

Yariv

Cappella

Joseph N

(2003) Do People Watch What They do not Trust? Exploring the association between news media skepticism and exposure. Communication Research 30(5): 504–529. DOI: 10.1177/0093650203253371.

42.

van Dijk

Teun A

(2017) How Globo Media Manipulated the Impeachment of Brazilian President Dilma Rousseff. Discourse & Communication 11(2): 199–229. DOI: 10.1177/1750481317691838.

43.

von Sikorski

Christian

(2018) Political Scandals as a Democratic Challenge| The Aftermath of Political Scandals: A Meta-Analysis. International Journal of Communication 12: 25. Available at: https://ijoc.org/index.php/ijoc/article/view/7100

44.

von Sikorski

Christian

Heiss

Raffael

Matthes

Jörg

(2020) How Political Scandals Affect the Electorate. Tracing the eroding and spillover effects of scandals with a panel study. Political Psychology 41(3): 549–568. DOI: 10.1111/pops.12638.

45.

Wagner

Markus

Tarlov

Jessica

Vivyan

Nick

(2012) Partisan Bias in Opinion Formation on Episodes of Political Controversy: Evidence from Great Britain. Political Studies 62(1): 136–158. DOI: 10.1111/j.1467-9248.2012.01002.x.

46.

Wolf

Zachary

(2019) The Whistleblower Complaint. Available at: https://edition.cnn.com/interactive/2019/09/politics/whistleblower-complaint-annotated/

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.11 MB