In the 2020 U.S. presidential election, the neighboring states of Wyoming, Idaho, and Utah all strongly supported Donald Trump, giving him respectively 70, 64, and 58 percent of their votes. But in all three states several counties opted for Joe Biden, a few by considerable margins (see the map below). All of these seeming exceptions are easily explained on the basis of demographic characteristics. Latah County, Idaho and Albany County, Wyoming, for example, are the sites of their states’ main universities, and college towns and nearby communities usually support candidates in the Democratic Party. Salt Lake County, Utah, in contrast, contains a major metropolitan area, which are also generally “blue” on electoral maps. Sparsely populated Grand County, Utah falls into neither category, but its main town, Moab, is a major center of outdoor recreation. Western communities with economies based on outdoor amenities also typically vote for Democrats. Teton County, Idaho falls into this same category.
The darkest shade of blue on this map is given to Blaine County, Idaho and Teton County, Wyoming. Their deciding demographic characteristic, as of Summit County Utah, is a variant of the environmental amenities theme, as all are sites of major ski resorts and their associated residential communities. What really distinguishes these three counties from their neighbors, however, is their wealth. As the somewhat dated map below posted shows, these are among the richest counties in the United States. With the exception of those whose wealth is largely derived from natural resources and farming, wealthy counties generally support Democratic candidates.
I wanted to see if ChatGPT could find and explain the seeming anomaly of low-density, white-dominated counties located in the conservative intermontane West strongly favoring Joe Biden over Donald Trump. I therefore made the following pointed, and hinting, request:
“Write a 500-word analysis of the geographical patterns found in the 2020 United States presidential election based on a map of all U.S. counties shaded by the margin of victory, paying attention to counties that were exceptions to the general geographical rules found on this map and taking into account per capita income.”
The essay that the chatbot gave in response is reproduced below. As can be seen, it fails to either locate or explain this interesting phenomenon.
Thinking that the chatbot would perform better if I limited its analysis to Utah, Idaho, and Wyoming, I gave it another chance. This response is also included below. Here again it failed its assignment. Although ChatGPT did notice and explain the seeming oddity of Teton County, Wyoming, it also included a major error in the same sentence: “County-level data shows that Trump won all but one county in the state, Teton County, which is known for its higher-income residents and a significant number of transplants from more liberal areas.” Perhaps ChatGPT did not notice that Biden also won Albany County, Wyoming because he took less than 50 percent of its votes. But Biden’s margin of victory here was still a reasonably solid 2.76 percent.
To sum up to this brief series, ChatGPT seems to be particularly bad at geographical analysis. Somehow, that does not surprise me.
ChatGPT Response 1:
The 2020 United States presidential election exhibited intriguing geographical patterns when analyzed using a county-level map shaded by the margin of victory. These patterns were influenced by various factors, including economic conditions such as per capita income. Let’s delve into the key observations, general trends, and notable exceptions:
- Urban-Rural Divide: A conspicuous urban-rural divide was evident. Urban and suburban areas, particularly along the coasts and in major metropolitan regions, tended to favor the Democratic candidate, Joe Biden. Conversely, rural and less densely populated areas, especially in the Midwest and the South, leaned toward the Republican incumbent, Donald Trump.
- Economic Centers: Counties encompassing major economic hubs, like Manhattan (New York County), Los Angeles County, and Cook County (Chicago), predominantly supported Biden. These urban centers typically have higher per capita incomes due to their concentration of economic activity, educational institutions, and diverse populations.
Several counties deviated from the general patterns, and these exceptions can be partly explained by considering per capita income:
- Rural Prosperity: In some rural counties, particularly in states like Wyoming, North Dakota, and parts of Texas, which benefit from natural resource industries (e.g., oil, gas, and agriculture), Trump received strong support despite their rural status. These exceptions underscore the economic diversity within rural America, where high per capita incomes can translate into political allegiance to Trump.
- Urban Economic Variation: In urban areas, especially in Rust Belt cities like Youngstown, Ohio, and Scranton, Pennsylvania, Trump gained ground in counties with lower per capita incomes. Economic hardship and the decline of manufacturing jobs in these regions likely contributed to this shift, illustrating how economic conditions can influence political preferences.
- Florida’s Diversity: Florida’s diverse economic landscape and a significant retiree population resulted in a mix of counties concerning per capita income and political leanings. While Miami-Dade County, with its high per capita income derived from tourism and international trade, experienced a shift toward Trump among some Hispanic voters, other counties with lower per capita incomes, such as Duval County (Jacksonville), swung toward Biden.
- Pennsylvania’s Suburban Complex: In Pennsylvania, Montgomery County, a suburban county with a high per capita income due to its proximity to Philadelphia, leaned decisively toward Biden, aligning with the urban-suburban pattern. However, nearby counties like Bucks and Northampton, with lower per capita incomes, displayed stronger support for Trump, suggesting a complex interplay of economic and demographic factors.
- Colorado’s Diversity: Colorado’s political landscape was influenced by factors like per capita income. While highly populated and affluent counties around Denver favored Biden, more rural counties with lower per capita incomes, especially in the Western Slope, remained staunchly Republican.
- Urban-Rural Divide in Swing States: In pivotal swing states like Wisconsin, Michigan, and Pennsylvania, the urban-rural divide played a substantial role. Notably, in Michigan, Macomb County, with a median income below the national average, shifted toward Trump, while higher-income suburban counties near Detroit leaned Democratic.
- Texas’s Suburban Shift: Texas saw suburban counties around major cities like Dallas and Houston, which typically have higher per capita incomes, shifting toward Biden. This shift challenged the notion of Texas as a solid Republican stronghold, emphasizing the impact of economic diversity in suburban areas.
In summary, the geographical patterns observed in the 2020 U.S. presidential election, as reflected in county-level margins of victory, revealed a dynamic interplay of economic conditions, demographics, and regional dynamics. While urban areas with higher per capita incomes generally favored Biden, exceptions in both rural and urban settings demonstrated the multifaceted nature of American politics. Understanding these exceptions is essential for a comprehensive analysis of the election results, as they underscore the complex relationship between economic well-being and political preferences in a diverse and evolving nation.
Prompt for second experiment: “Write a 500-word essay analyzing the 2020 presidential election returns from Idaho, Wyoming, and Utah using country-level data.”
ChatGPT Response 2.
Title: Analyzing the 2020 Presidential Election Returns in Idaho, Wyoming, and Utah
The 2020 United States presidential election was one of the most highly anticipated and closely watched elections in recent history. While national-level analysis often dominates discussions, it is equally important to examine the results at the state level to gain a deeper understanding of the political landscape. In this essay, we will analyze the 2020 presidential election returns in the states of Idaho, Wyoming, and Utah using county-level data, shedding light on key trends, demographics, and political dynamics that shaped the outcomes in these predominantly conservative states.
Idaho: A Stronghold for Republicans
Idaho, known for its deep-rooted conservatism, continued its tradition of favoring the Republican candidate in the 2020 election. With a state-level margin of over 30 percentage points in favor of Donald Trump, it was one of the most solidly Republican states in the nation. County-level data reveals that the Republican dominance was consistent throughout the state, with Trump carrying the majority of counties.
One notable observation from the Idaho data is the urban-rural divide. While metropolitan areas like Ada County (Boise) leaned more Democratic, rural counties, particularly in the eastern part of the state, overwhelmingly supported Trump. This pattern reflects a broader national trend seen in many states, where urban areas tend to favor Democratic candidates, while rural areas lean Republican.
Furthermore, Idaho’s predominantly white population played a significant role in shaping the outcome. The lack of racial diversity in the state contributed to a more homogeneous political landscape, with racial and ethnic minorities having less influence on the election outcome compared to more diverse states.
Wyoming: A Republican Stronghold with Unique Dynamics
Wyoming, like Idaho, is considered a Republican stronghold, but it exhibits some unique dynamics. With a staggering margin of over 40 percentage points in favor of Trump, Wyoming was one of the most reliably red states in the 2020 election. County-level data shows that Trump won all but one county in the state, Teton County, which is known for its higher-income residents and a significant number of transplants from more liberal areas.
A striking feature of Wyoming’s election returns is its low population density. The state’s vast, sparsely populated rural areas play a crucial role in shaping the political landscape. In such regions, where traditional values and limited government intervention are often prized, the Republican message resonates strongly.
Another factor to consider is Wyoming’s energy industry, which is a significant contributor to the state’s economy. Trump’s promises to support fossil fuels and reduce environmental regulations likely bolstered his support among voters in this state, where energy policy is of paramount importance.
Utah: A Conservative State with Nuanced Tendencies
Utah is another conservative state, but it has shown more nuanced political tendencies. While Trump comfortably won Utah, his margin was smaller than in Idaho and Wyoming. County-level data reveals some interesting insights. Utah’s population centers, including Salt Lake County, leaned more Democratic, driven in part by a younger and more diverse demographic.
One notable aspect of Utah’s political landscape is the presence of a significant independent and moderate Republican constituency. This group, often referred to as “Never Trumpers,” was less enthusiastic about the president. The presence of prominent figures in the state’s Republican establishment who openly criticized Trump may have contributed to this trend.
In analyzing the 2020 presidential election returns in Idaho, Wyoming, and Utah using county-level data, it is clear that these predominantly conservative states exhibited unique political dynamics. Idaho and Wyoming remained solid Republican strongholds, with their rural areas and homogeneous populations contributing to the overwhelming support for Donald Trump. Meanwhile, Utah, while still conservative, showed more nuanced tendencies, with urban areas and a moderate Republican constituency influencing the election outcome.
Understanding these state-level dynamics is crucial for comprehending the broader political landscape in the United States. The 2020 election provided valuable insights into the interplay of demographics, regional characteristics, and political ideologies that shape electoral outcomes in these states. As we look ahead to future elections, it is essential to continue analyzing state-level data to gain a more comprehensive understanding of the American political landscape.