Howey
Gold Member
- Mar 4, 2013
- 5,481
- 761
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I just read in another thread where a racist claimed blacks are less educated and poorer than whites. That led me to question the claim, knowing the lack of intellect and education, particularly in their lack of grasp of the English language, displayed by this forum's Trump supporters.
I had every right to question The claim.
The analysis shows that Trump counties are places where white identity mixes with long-simmering economic dysfunctions.
One element common to a significant share of his supporters is that they have largely missed the generation-long transition of the United States away from manufacturing and into a diverse, information-driven economy deeply intertwined with the rest of the world.
The 10 Variables Most Closely Linked to a County’s Support for Donald Trump
A correlation of 1 means the variable is a perfect indicator of Trump support.* Negative correlations are shown in red.
VARIABLE CORRELATION
White, no high school diploma
0.61
“Americans”
Percent reporting ancestry as “American” on the census
0.57
Mobile homes
Percent living in a mobile home
0.54
“Old economy” jobs
Includes agriculture, construction, manufacturing, trade
0.50
History of voting for segregationists
Support for George Wallace (1968)
0.47
Labor participation rate
–0.43
Born in United States
0.43
Evangelical Christians
0.42
History of voting for liberal Republicans
Support for John B. Anderson (1980)
–0.42
White Anglo-Saxon Protestants
Whites with European non-Catholic ancestry
Mr. Trump has performed well thus far in Appalachian coal counties and in rural parts of Alabama and Mississippi, which are coping with economic and social dysfunctions like high unemployment rates and heroin addiction. But the Upshot analysis also shows the common thread between those places and more urban locations where Mr. Trump has either done well or is projected to.
In Revere, Mass., a working-class suburb of Boston, Mr. Trump won 73 percent of the Republican primary vote.
The high proportion of whites without a high school diploma in these places — the single strongest predictor of Trump support of those we tested — has lasting consequences for incomes, for example. The education pay gap starts small when people are early in their careers before widening over the decades of their working lives. College graduates are less likely to become unemployed and more likely to find a new job quickly if they do, and there are comparatively fewer of them in Trump-land.
Likewise, a better predictor of strong Trump support than a standard-issue economic indicator like the unemployment rate is a high proportion of working-age adults who aren’t working (the correlation was strong for both men and women).
To be counted as unemployed, a person must have actively looked for work in the last month. But “not working” is a broader definition that would also include, for example, people who are discouraged by what seem like grim job prospects; who are living at home tending to the house; or who are disabled and stay home while receiving government assistance.
Nationally, 23 percent of the 25-to-54-year-old population was not working in March, up from 18 percent in 2000. The areas where Trump is most popular appear to be at the forefront of that trend.
Despite evidence that some individual Trump voters are driven by racial hostility, this analysis didn’t show a particularly powerful relationship between the racial breakdown of a county and its likelihood of voting for Trump. There are Trump-supporting counties with both very high and very low proportions of African-Americans, for example.
I had every right to question The claim.
The analysis shows that Trump counties are places where white identity mixes with long-simmering economic dysfunctions.
One element common to a significant share of his supporters is that they have largely missed the generation-long transition of the United States away from manufacturing and into a diverse, information-driven economy deeply intertwined with the rest of the world.
The 10 Variables Most Closely Linked to a County’s Support for Donald Trump
A correlation of 1 means the variable is a perfect indicator of Trump support.* Negative correlations are shown in red.
VARIABLE CORRELATION
White, no high school diploma
0.61
“Americans”
Percent reporting ancestry as “American” on the census
0.57
Mobile homes
Percent living in a mobile home
0.54
“Old economy” jobs
Includes agriculture, construction, manufacturing, trade
0.50
History of voting for segregationists
Support for George Wallace (1968)
0.47
Labor participation rate
–0.43
Born in United States
0.43
Evangelical Christians
0.42
History of voting for liberal Republicans
Support for John B. Anderson (1980)
–0.42
White Anglo-Saxon Protestants
Whites with European non-Catholic ancestry
Mr. Trump has performed well thus far in Appalachian coal counties and in rural parts of Alabama and Mississippi, which are coping with economic and social dysfunctions like high unemployment rates and heroin addiction. But the Upshot analysis also shows the common thread between those places and more urban locations where Mr. Trump has either done well or is projected to.
In Revere, Mass., a working-class suburb of Boston, Mr. Trump won 73 percent of the Republican primary vote.
The high proportion of whites without a high school diploma in these places — the single strongest predictor of Trump support of those we tested — has lasting consequences for incomes, for example. The education pay gap starts small when people are early in their careers before widening over the decades of their working lives. College graduates are less likely to become unemployed and more likely to find a new job quickly if they do, and there are comparatively fewer of them in Trump-land.
Likewise, a better predictor of strong Trump support than a standard-issue economic indicator like the unemployment rate is a high proportion of working-age adults who aren’t working (the correlation was strong for both men and women).
To be counted as unemployed, a person must have actively looked for work in the last month. But “not working” is a broader definition that would also include, for example, people who are discouraged by what seem like grim job prospects; who are living at home tending to the house; or who are disabled and stay home while receiving government assistance.
Nationally, 23 percent of the 25-to-54-year-old population was not working in March, up from 18 percent in 2000. The areas where Trump is most popular appear to be at the forefront of that trend.
Despite evidence that some individual Trump voters are driven by racial hostility, this analysis didn’t show a particularly powerful relationship between the racial breakdown of a county and its likelihood of voting for Trump. There are Trump-supporting counties with both very high and very low proportions of African-Americans, for example.
I'll vote Clinton as I hate savages and idiocy.
