In the aftermath of one of the most surprising elections in U.S. history, one factor should have predicted it all.
By Frederik Forrai Ørskov
Places like Mahoning County in Ohio and Macomb County in Michigan have not made many headlines in the coverage of American politics. Despite this, counties like these are crucial to comprehending how the pollsters got it wrong and Donald Trump triumphantly swept the electoral college in November.
So says Michael McQuarrie, a sociologist at the London School of Economics who has done extensive work on community organizing and development and is a prominent voice in the post-election debate on the causes of liberal electoral defeat. He sees both counties as symptomatic of the breakdown of Barack Obama’s Mid-American constituency, a breakdown that ultimately turned Hillary Clinton into an entirely coastal candidate and Donald Trump into the President of the United States.
Both counties are located in the so-called Rust Belt—the name given to a region marred by urban decay and post-industrial economic decline stretching roughly from the Great Lakes to the Upper Midwest and from western New York State to Chicago. Both counties saw large shifts from Democrat to Republican in the recent election; Macomb County voted solidly Republican although it had been won by Democrats in 2008 and 2012, and although Hillary Clinton held on—just barely—to Mahoning County, she only obtained 49.8 percent of the votes there, compared to Obama’s 63.5 percent four years earlier. Both counties are urban areas in which the Clinton campaign under-performed significantly compared to the average electoral outcome in cities nation-wide.
Mahoning County is home to Youngstown, a city located mid-way between Pittsburgh and Cleveland whose decline from thriving steel town to post-industrial slump has been eminently portrayed by Bruce Springsteen. Just like the northern suburbs of Detroit making up the electorate of Macomb County, the inhabitants of Mahoning County are predominantly white, middle-class workers. It is representative of …
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