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posted by janrinok on Thursday December 07 2017, @01:05AM   Printer-friendly
from the and-a-polite-discussion-ensued... dept.

Recently published in Journal of Social and Political Psychology by Thomas F. Pettigrew seeks to understand the psychological profile of Trump supporters:

The Trump movement is not singular within the United States (the Know Nothing movement in the 1850s, the Wallace movement in the 1960s, and the more recent Tea Party Movement). Moreover, other democracies have seen similar movements (e.g., Austria's Freedom Party, Belgium's Vlaams Blok, France's National Front, Germany's Alternative for Germany Party (AfD), and Britain's U.K. Independence Party (UKIP).

In virtually all these cases, the tinder especially involved male nativists and populists who were less educated than the general population. But this core was joined by other types of voters as well. Five highly interrelated characteristics stand out that are central to a social psychological analysis – authoritarianism, social dominance orientation, outgroup prejudice, the absence of intergroup contact and relative deprivation.No one factor describes Trump's supporters. But an array of factors – many of them reflecting five major social psychological phenomena can help to account for this extraordinary political event: authoritarianism, social dominance orientation, prejudice, relative deprivation, and intergroup contact.


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  • (Score: 2) by janrinok on Thursday December 07 2017, @05:57AM (1 child)

    by janrinok (52) Subscriber Badge on Thursday December 07 2017, @05:57AM (#606665) Journal
    Have you read this? [soylentnews.org]
    --
    I am not interested in knowing who people are or where they live. My interest starts and stops at our servers.
    Starting Score:    1  point
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    Total Score:   2  
  • (Score: 1, Insightful) by khallow on Thursday December 07 2017, @07:15AM

    by khallow (3766) Subscriber Badge on Thursday December 07 2017, @07:15AM (#606687) Journal
    The problem is that it's garbage. The author grinds away at his ideological ax throughout the paper (for example, using terms like "right/left winger" and "dog whistles" to name a couple that I saw with a quick glance). And no attempt has been made to distinguish subgroups. I also see all kinds of minor errors that just shouldn't make their way into the paper, like making an assertion [soylentnews.org] about automation and never revisiting the subject again, or calling a slight correlation "correlates highly".

    Not surprisingly, then, support for Trump correlates highly with a standard scale of modern racism (r = +.48; Van Assche & Pettigrew, 2016).

    The final straw though is the blatant slant to the interpretation of results. For example,

    Consider again the U.K. Brexit vote. Urban areas, such as London, with large, established immigrant populations voted strongly to remain in the European Union (EU); while areas with relatively few immigrants voted heavily to leave the EU. But when a longitudinal analysis is applied, the key variable emerges: the speed of change in the immigrant population. Areas with modest immigrant populations in 2000 that had witnessed more than a 200% rise in immigrants by 2015 voted an astounding 94% to leave the EU (Economist Staff, 2016). This striking result is an example of the delicate balance between threat and contact – the dual effects of diversity (Green, Sarrasin, Baur, & Fasel, 2016; Pettigrew & Hewstone, 2017; Wagner, Christ, Pettigrew, Stellmacher, & Wolf, 2006). London and other major English cities had had long experience with immigrants, and had increased their diversity relatively gradually. Time had reduced the sense of threat and enhanced positive intergroup contact. But for small towns and rural districts with a sudden and rapid entry of immigrants, perceived threat prevailed and optimal contact was as yet minimal.

    A quite similar process occurred in small Midwestern towns with rapid increases in Latino immigration. According to Adamy and Overberg (2016b), areas whose diversity index rose by 150% witnessed a 67% vote for Trump. Consider Arcadia, Wisconsin, that had job growth – not restricted jobs (Adamy & Overberg, 2016a). Arcadia’s plentiful jobs attracted rapid in-migration from below the Mexican border – roughly 1,500 miles away. The resulting perceived threat, unalleviated by a period of intergroup contact, made many rural and small-town White Midwesterners respond positively to Trump’s harsh anti-immigrant rhetoric. This interpretation is supported by the macro-findings of Rothwell and Diego-Rosell (2016) discussed above.

    In other words, areas with huge increases in immigrant population voted for Brexit and for Trump in their respective countries. He chooses to interpret that as meaning that the native population hasn't yet had experience dealing with recent immigrants rather than that their experience with recent immigrants is going poorly.