Before looking at the correlation analyses, it is important to understand the distribution of self-placement on the left-right political scale. Five was the most common placement number for both countries, in a range from 0-10 with 0 being ‘left’ and 10 being
‘right.’ In Round 7 of the Hungarian sample, 305 individuals did not give a response, and in Round 7 of the UK sample 231 individuals did not respond. Round 7 of the Hungarian sample showed that 526/1388 individuals, or 39.73%, chose the middle value. In the UK sample, 765/1938 individuals, or 39.47%, chose the middle value. It can be said, then, that more than a third of the survey respondents were unsure of their political leanings, and/or were likely not overly involved with the country’s political situation. Also, 18.72% of Hungarian respondents and 10.65% of UK respondents either refused to answer entirely or were unsure of their answer in Round 7. In Round 8 of the Hungarian sample, 285 individuals did not give a response, and in Round 8 of the UK sample 151 individuals did not respond. Round 8 of the Hungarian sample showed that 346/1291 individuals, or 26.8%, chose the middle value, almost exactly 10% less than in Round 7. In the UK sample, 696/1741 individuals, or 39.98%, chose the middle value. The distribution of the Hungarian sample for both rounds 7 and 8 can be found in Table 3.2 and of the UK sample in Table 3.3.
120 Table 3.2: Distribution of left-right political scale self-placement in Hungarian sample Rounds 7 & 8
Scale
Table 3.3: Distribution of left-right political scale self-placement in UK sample Rounds 7 & 8 Scale
There is a clear difference between the distributions of the two samples. The UK sample, as can be seen, is relatively evenly distributed between left-wing (0-4) and right-wing (6-10) self-placement for both Rounds 7 and 8. The Hungarian sample, on the other hand, shows a different trend: for Round 7, 21.3% of the sample self-describes as somewhere on the left-side of the spectrum, while 38.9% describe as being on the right-side of the left-right political scale. For Round 8, 22.22% of the sample self-describes as falling on the left-side of the scale, while 50.98% place themselves on the right-side of the
121 political scale. Of these, 14.73% self-describe as what is being considered for the purposes of this study as far-right, up from 8.91% two-years prior.
The results of the UK show that distribution of the scale stays fairly consistent from Round 7 to Round 8. The distribution is also centred around the middle of the scale showing lower values on the extremes of the scale. The results, however, showed a slightly larger change in Hungary between 2015 and 2017. Firstly, more than 10% less people chose the middle-value in 2017. While could be due to differences in the sample, this could also be taken to mean that around 13% of people were more confident in their political leanings.
These were firmly applied to the right-side of the scale, with all values increasing; most notable, “10” nearly doubled, from 5.66% to 10%. This could be due to differences in sampling, as they did not sample the same respondents for both rounds, but could also indicate a shift to the right in the Hungarian population. Additionally, this could mean a different interpretation of ‘10’ in the Hungarian population: this could be interpreted by respondents as highly conservative (a Fidesz supporter), for example, and not as far-right.
Comparing the Hungarian and UK samples highlights the more centrist tradition in UK politics. This is reflective of the party tradition in the UK, of the moderate-right Tories and moderate-left Labour. It could very-well be that answers to this question are more along the line of political voting preference in the minds of respondents, hence self-identification reflecting the political identity of the party they tend to support, not necessarily perfectly reflecting their own attitudes and political ideology. This would also explain the higher amount of right self-identification in Hungary, given the constant shift towards the far-right of the Fidesz party.
122 3.3.2 Independent Variable Distribution
The three independent variables used in these analyses were satisfaction with life, opinion of whether immigrants are good or bad for the country’s economy, and opinion of whether immigrants undermine or enrich a country’s cultural life.
Satisfaction with life was measured on an 11-point scale, with 0 being ‘extremely dissatisfied’ and 10 being ‘extremely satisfied.’ Table 3.4 shows the variable distribution for the both rounds 7 and 8 for the Hungarian sample and Table 3.5 for the UK sample, showing both the total number of respondents and corresponding percentages for each value. By looking at the percent distributions, it becomes obvious that respondents in the UK sample were largely more satisfied with their lives than in the Hungarian sample, which is true across both Rounds.
Table 3.4: Distribution for satisfaction with life for both rounds of the Hungarian sample, where 0 is extremely dissatisfied and 10 is extremely satisfied.
Frequency R7 Percentage R7 Frequency R8 Percentage R8
0 38 2.36 22 1.41
1 20 1.24 17 1.09
2 94 5.83 52 3.32
3 146 9.06 86 5.5
4 126 7.82 102 6.52
5 336 20.86 216 13.8
6 200 12.41 230 14.7
7 271 16.82 328 20.96
8 222 13.78 302 19.3
9 80 4.97 105 6.71
10 77 4.78 105 6.71
TOTAL 1611 100 1565 100
123 Table 3.5: Distribution for satisfaction with life for both rounds of the UK sample, where 0 is extremely dissatisfied and 10 is extremely satisfied.
Frequency R7 Percentage R7 Frequency R8 Percentage R8
0 21 .97 13 .69
1 14 .65 18 .95
2 33 1.52 25 1.32
3 60 2.77 52 2.75
4 76 3.51 76 4.02
5 203 9.36 143 7.57
6 179 8.26 148 7.83
7 432 19.93 337 17.83
8 562 25.92 548 28.99
9 351 16.19 309 16.35
10 237 10.93 221 11.69
TOTAL 2168 100 1890 100
Opinion of whether immigrants are good or bad for the country’s economy was measured on an 11-point scale, with 0 being ‘bad for economy’ and 10 being ‘good for economy.’ Table 3.6 shows the variable distribution for both Rounds 7 and 8 for the Hungarian sample and Table 3.7 for the UK sample, showing both the total number of respondents and corresponding percentages for each value. The distribution reveals that Hungarian respondents were largely more pessimistic about immigrants’ effect on the economy than were UK respondents. Again, while these data sets cannot provide a perfect comparison, observing the results of Rounds 7 and 8 reveals a marked increase in pessimism among the Hungarian sample and an increase in optimism in the UK sample, which will be discussed in more detail below.
124 Table 3.6: Distribution for opinion on whether immigrants are good or bad for economy for both rounds of the Hungarian sample, where 0 is ‘bad for the economy’ and 10 is ‘good for the economy.’
Frequency R7 Percentage R7 Frequency R8 Percentage R8
0 186 12.32 308 21.1
Table 3.7: Distribution for opinion on whether immigrants are good or bad for economy for both rounds of the UK sample, where 0 is ‘bad for the economy’ and 10 is ‘good for the economy.’
Frequency R7 Percentage R7 Frequency R8 Percentage R8
0 161 7.51 79 4.24
Opinion of whether immigrants undermine or enrich the cultural life of a country was measured on an 11-point scale, with 0 being ‘cultural life undermined’ and 10 being
‘cultural life enriched.’ Table 3.8 shows the variable distribution for both Rounds 7 and 8 for the Hungarian sample and Table 3.9 for the UK sample, showing both the total number of respondents and corresponding percentages for each value. The distribution pattern is largely the same for both data sets, with Hungarian respondents being somewhat more unsure than UK respondents (given the higher percentage of the middle-choice ‘5’) in
125 Round 7. This is likely due to the lower frequency of immigration into Hungary than into the United Kingdom.
In Round 8, the UK sample is strongest around values 5-8, suggesting a moderate optimism about the effects of immigrants on cultural life. These results are not strikingly different from the results of Round 7: we do see a drop by half in the zero-value from 7.9 percent to 4 percent along with a rise in positive values and decline in negative values, but the changes are relatively marginal. Indeed, these results support similar findings by large-scale surveys in the UK, such as findings by Ipsos MORI that Britons are becoming more positive about the impacts of immigration on the UK (Kaur-Ballagan, Gottfried, and Holden, 2019). However, according to Goodwin and Milazzo (2017), negative feelings towards immigrants began to be more pronounced after the 2004 accession of Central and Eastern European countries to the European Union, after which many people came to the UK. A decade later, after 2015, these concerns were strengthened by the refugee crisis, especially given the anti-EU and anti-immigrant campaigning by parties like UKIP (Goodwin and Milazzo, 2017). The results here, however, show the opposite effect: that views toward immigration, at least in terms of its effect on cultural life, are becoming more positive since 2015.
The Hungarian sample, however, paints a different picture. The Round 7 results reveal an uncertainty among people about immigrants and whether they have an effect on cultural life. In Round 8, however, the results become markedly pessimistic. The 0-point, suggesting immigrants undermine cultural life completely, went from 4.61 percent in round 7 to 16.86 percent in round 8. The rest of the values at the lower-end of the scale, number 2-4, increased in percentage while the rest lowered. This suggests that the xenophobic and nativist nation-wide anti-migrant campaigns of the authoritarian Fidesz government, beginning in the summer of 2015, indeed worked to influence the Hungarian people. This
126 is also a frightening demonstration of the lack of alternative dialogue and discourse in Hungary, especially in the media, leading to the indoctrination of a large percentage of Hungarians.
Table 3.8: Distribution for opinion on whether immigrants undermine or enrich the cultural life of a country for both rounds of the Hungarian sample, where 0 is ‘undermine cultural life’ and 10 is ‘enrich cultural life.’
Frequency R7 Percentage R7 Frequency R8 Percentage R8
0 63 4.17 248 16.86
Table 3.9: Distribution for opinion on whether immigrants undermine or enrich the cultural life of a country for both rounds of the UK sample, where 0 is ‘undermine cultural life’
and 10 is ‘enrich cultural life.’
Frequency R7 Percentage R7 Frequency R8 Percentage R8
0 153 7.16 73 4.0
127 3.4CONTROL MEASURES
As a range of demographic factors can influence placement on the left-right political scale, control measures were used in both multivariate analyses. All control measures were recoded before running statistical tests and missing data was excluded, in order to conserve degrees of freedom within the model.
Predictors included gender, age, employment, partnership, and years in education (Table 3.10, Table 3.11, and Table 3.12). Gender and employment were transformed into binary measures, while partnership was found by combining those individuals with legal marital status and those cohabiting with a partner. Age and years in education are scale measures. Predictors were tested for multicollinearity by examining Variable Inflation Factors in SPSS. No predictors or independent variables showed multicollinearity in either the Hungarian or UK sample.
Employment emplrl Categorical Employed = 1, Unemployed = 0 Partnership Marital
Status
marsts Categorical Combination of legal marital status and those