The results from the analysis, a regression model covering all CEE countries, can be seen in Fig. 2. The vast majority of independent sociodemographic variables are statistically insignificant. The only significant variable was age: support for technocratic attitudes increased along with age. However, the effect was relatively small.
Second, in terms of the various measures of authoritarianism, both political authoritarianism and hardline military authoritarianism are statistically significant. The weaker the attitudes supporting it, the weaker the technocratic attitudes (Fig. 2; Table 1, Model 1 in the Appendix). Interestingly, the variable measuring the duty-based normative dimension of democracy was not found to be significant.
The democratic deficit variable, measuring the difference between the importance placed on the ideal of democracy and satisfaction with its fulfilment/realization in a given country, was found significant. The greater the democratic deficit, the stronger the support for technocratic governance. Finally, distrust in particular political institutions was found to be significant as well. The more people distrust political institutions, the stronger technocratic attitudes are.
FIGURE 2 HERE
At face value, these results do not appear surprising. Other studies expected and predicted the association between authoritarian and technocratic attitudes (Chiru and Enyedi, 2022; Vittori and Paulis, 2024). Moreover, the fact that democratic deficit is correlated with technocracy-supporting attitudes is not unforeseen either. Technocracy seems like an appealing option to those who are dissatisfied with how democracy works but are supportive of the general ideal of democracy. Given how the populace in CEE countries has been dissatisfied with political transformation, this does not come as a surprise. Yet, what is somewhat surprising is the combination of the results, which do not seem compatible. If support for technocratic governance stems from authoritarianism, this is incompatible with the fact that another source is the democratic deficit. In other words, why would hardline authoritarians exhibit attitudes of “democratic deficit”? If someone is hardline authoritarian, why would he be concerned about democracy at all? A similar contradiction can be found in other studies, where both authoritarianism and political efficiency are sources of technocracy. If support for technocracy stems from authoritarian attitudes, how is this compatible with the belief that the political system should be more responsive to the demands of citizens? These two findings are, similarly, in conflict or contradiction (Chiru and Enyedi, 2022).
These results may suggest heterogeneity in the data; different subgroups in the data could have different and incompatible attitudes. Nevertheless, both groups support technocratic governance, albeit for different reasons. The upshot is these results also hint at multiple paths for reaching technocratic attitudes, that there could be heterogeneity in the data, that is, multiple forms of technocratic attitudes. This hypothesis is explored in the following section.
4.1 Analysis of heterogeneity: latent class model
The analysis presented above implies that in relation to the understanding of democracy, there may be multiple sources of technocratic attitudes. However, regression models, due to being additive, are not ideal for uncovering this heterogeneity. To answer these questions, a latent class analysis (LCA) was therefore applied to the CEE countries instead to reveal this heterogeneity in the data – should it exist. For the analysis, the LatentClassAnalysis.jl package was used and performed in Julia[2].
The goal of an LCA is to identify unobserved classes based on observed manifest variables. LCA is based on a probabilistic model and allows for the classification of observations into these latent groups (Muthén and Muthén, 2017). The first step of LCA is to estimate the number of latent classes. The next step is a description of these classes.
There is no one exclusive criterion in determining the number of latent classes. Most often, information criteria are used to estimate the number of latent classes, taking into account the interpretability of the model as well (Vermunt and Magidson, 2004; Zhang et al., 2018). For the purpose of this analysis, the following criteria were considered: the Akaike Information Criterion (AIC) and the sample-adjusted Bayesian Information Criterion (BIC). The goal is to select a solution (in terms of number of classes) that minimizes these information criteria.
The first step aimed to use all the countries and perform the analysis on the whole sample. The variables used in the analysis were those at the core of the previous regression analysis: technocratic attitudes, perceived democratic deficit, satisfaction with institutions, the duty-obedience dimension and two measures of authoritarianism: political and military. Variables measuring democratic deficit and obedience-duty dimensions were recoded into quartiles since the other variables are in the survey data as 4-point scales. Thus, the goal was to have items on the same scale.
The first step was to identify a solution that minimizes the information criterion. However, this was not achieved because each additional class always resulted reduced information criterion. However, this is not uncommon in the case of complex samples, which is the case of this multiple-country analysis. In these cases, it is advised to look for an “elbow” point of diminishing returns, such as in a principal component analysis (Nylund-Gibson and Choi, 2018, p. 9). Based on this criterion, a solution containing five classes was identified; adding additional classes beyond five increased the quality of the model only minimally.
The results are presented in Fig. 3: Fig. 3a shows the profile of the five classes, Fig. 3b shows the process of searching for the best class and Fig. 3c shows the profile of the five respective classes based on the technocratic attitudes variable.
Of the five classes, only the two relevant classes were labelled: authoritarian technocrats and democratic technocrats. These two classes had above-average technocratic attitudes and can be seen both in Figs. 3a and 3c. As shown in Fig. 3a, the authoritarian technocrats are not only very strongly technocratic but also the most authoritarian of all classes. Compared to other classes they also relatively strongly support the obedience understanding of democracy. The other variables are not particularly significant in comparison with other classes. This class accounted for 11% of the total sample.
The second group consists of democratic technocrats. This group is characterized by above-average and strong technocratic attitudes. However, this group is also very weak or even anti-authoritarian in both dimensions measuring authoritarianism. Members of this class are also the class most strongly opposing the obedience understanding of democracy. The final characteristics that stand out are the strongest dissatisfaction with institutions and the strongest perceived democratic deficit. The characteristic feature of this class is that it combines a belief in technocratic governance with dissatisfaction with political institutions, a belief in democracy but dissatisfaction with its current functioning, non-authoritarian attitudes and an understanding of democracy that rejects duty and obedience. The size of the group is 25% of the overall sample.
These two classes share one common characteristic—technocratic attitudes. However, the two groups have incompatible and opposing profiles as regards all of the other characteristics.
FIGURE 3
FIGURE 4
The disadvantage of this solution is that the package from Julia does not allow weighting by individual countries. This is also not possible with any other freely available packages (e.g., poLCA in R). The second limitation is that the number of classes was identified based on qualitative criteria. Although the recommendation in the literature was followed (in cases of complex and large data sets, look for the point of diminishing return), two robustness tests were performed. First, the results were checked to see whether the results held for 6 or 7 class solutions. The results (not reported here) show that the two most technocratic classes always have the opposite profile in these other solutions as in the analysis above. Finally, the second robustness test replicated the analysis on a single country for certainty. Therefore, a single country was selected as a robustness test—the Czech Republic. The country is often mentioned as a case of technocratic populism, so it should be ideal case (Buštíková and Guasti, 2019; Havlík, 2019; Drápalová and Wegrich, 2021).
The results of the analysis, based on BIC, found a solution containing five classes, the profile of which is shown in Fig. 4. The AIC information criterion identified seven classes. Here, we will work with a solution with five classes (I will comment on the seven-class solution below).
The model with five classes in the Czech Republic is identical or very similar to the results from all CEE countries in terms of the main classes. Again, these are two classes with above-average technocratic attitudes and whose profile is very similar to the profiles identified in Fig. 3 on the general sample, including all countries. One of these classes has the profile of authoritarian attitudes, the other combines technocratic attitudes with democratic deficit, dissatisfaction with political institutions and non-authoritarian attitudes. In other words, these results in the Czech Republic corroborate the results of the whole sample of CEE countries. The only substantive difference is the size of the respective classes: the Czech authoritarian technocratic group was 9%, whereas the democratic technocratic class had a size of 15%.
As mentioned above, the AIC information criteria favoured a 7-class solution. When this solution was applied, the results were the same in terms of substantive results: two latent classes with strongly technocratic attitudes were identified with the same pattern of attitudes as the 5-class solution described above.
In summary, there are two distinct types of technocratic attitudes. One stems from authoritarian attitudes, while the other is clearly non-authoritarian and associated with a perceived democratic deficit. In other words, the results confirm heterogeneity in the data related to technocratic attitudes.
4.2 Analysis of heterogeneity: regression model
This analysis thus shows that there is a type of attitude that is referred to here as “democratic technocracy”. If anything characterizes it based on the above analyses (e.g., Fig. 3), it is a strong perception of a democratic deficit (the gap between the democratic ideal and reality), a rejection of an obedience-based understanding of democracy and dissatisfaction with political institutions. These traits characterize these technocratic democrats the most.
However, the original multilevel ordinal regression model can also test these differences and characteristics. Therefore, this model included the interaction between the democratic deficit and both an obedience understanding of democracy and dissatisfaction with institutions. The interaction between these variables was included because these variables significantly differentiate the above-mentioned profile of democratic technocrats. The results are shown in Figs. 5 (Appendix Table 1, Model 2) and 6 (Appendix Table 1, Model 3).
FIGURE 5
FIGURE 6
For example, Fig. 5 shows that there are two paths that lead to an increase in technocratic attitudes. Those who are high on the democratic deficit scale and think obedience/duty does not belong to democracy are likely to have an increased probability of technocratic attitudes. However, those who are low on democratic deficit and support obedience are likely to have higher technocratic attitudes as well. This interaction is not and cannot be a rigorous test of two groups of authoritarian and democratic technocrats—unlike LCA, regression analysis does not allow for this. However, two trends can be observed: technocratic attitudes can be achieved (a) by rejecting obedience to authority and expressing a strong democratic deficit and (b) through a low democratic deficit and support for the obedience dimension. This pattern can also be clearly seen in LCA analysis.
In other words, the regression model’s results also make it possible to identify the two types of technocratic attitudes. These attitudes are united only by strong technocracy, but otherwise they are oppositional in other measured respects.
Ultimately, the results could lead to an interpretation that the two types of technocracy mentioned above differ in degree. This would correspond to Andrea Caramani’s thesis that extreme forms of technocracy are authoritarian but milder forms may be compatible with democracy, or that authoritarianism can be associated with technocracy only from a certain degree of technocracy onwards. This idea would be consistent with the finding that the democratic form of technocracy is somewhat milder in the latent class profiles. However, there is a caveat. If we look at Fig. 3c, that is, the degree of technocratic attitudes by class, then the authoritarian technocrats are more technocratic—the share of the strongest category of technocrats is 80% compared to less than 50% for democratic technocrats. However, there are 2.5 times more of the latter than the former. Therefore, the number/counts of those who strongly support technocracy is similar in both classes. Nevertheless, the class of democratic technocrats is broader and includes those with milder attitudes. It may be that the authoritarian version of technocracy exists only in its extreme form, while the democratic version exists both in its strongly technocratic form as well as its softer version.
The results of the analysis show that there are two types of technocratic attitudes. These results are stable with regard to a variety of robustness tests: (i) The LCA results are stable even for a different number of latent classes (6 and 7 classes). (ii) The LCA results are the same even when applied to only one country. (iii) The same conclusions can also be reached by applying interactions in the original regression model. (iv) The results are stable with and without imputation. And finally (v) The results were also identical when contextual variables were included.
There are also certain limitations. Only one variable is available for measuring technocratic attitudes. It would also be interesting to know to what extent people distinguish between different forms of expertise. Unfortunately, there are limitations to the existing EVS data in this regard. Another limitation is that the data does not allow us to further investigate what democratic technocracy actually means and how people imagine it. The data suggests that it is anti-authoritarian and pro-democratic. But it is difficult to say more beyond this. In other words, the data does not allow for a deeper understanding of the attitude mentioned. Here are a few alternatives. It may be that citizens want politicians to be replaced by non-political experts from time to time—this is consistent with the great popularity of caretaker "expert" governments. Or it may be a deeper conviction about the advantages of experts in any form of politics and governance. Some case studies suggest the latter option (Durnová, 2021; Lokšová and Galčanová Batista, 2021). Case studies of local governance show, for example, that technocratic governance is perceived positively at the local level and even perceived as a democratic innovation because it allows for contestation and potentially changes to ossified and unresponsive political decision-making. However, this goes beyond the scope of this analysis and is a question for further research.