Position Paper 1 | Political Pundits

Journalism aims to help people understand what is happening in the world, but there has been a growing trend of consumers expecting journalists to tell them what will happen. These predictions, based on polling, voting histories, demographics, economics, interviews, fundraising, and other evidence, center around election forecasts, political candidates, and crises. When grounded in facts and data and treated as probabilities rather than certainties, predictive journalism may teach audiences something valuable about the core forces driving election results. 

Similar to this growing trend, there has been a prevalence of "hot takes"––or a strongly worded opinion or reaction––in modern news coverage, which are designed to be provocative and attract attention. To say that social media has given countless people a large platform to spread political commentary and speculation is an understatement. These individuals––referred to as political pundits––provide predictions, opinions, analysis, and commentary on political issues and events on the grounds of hot takes instead of evidence-based reporting. This type of media coverage shapes public opinion on important issues and events, which shows how difficult it can be to separate informed predictions from political commentary.

When looking at two prominent commentators––Ben Shapiro and Rachel Maddow––we can see how differently they interpret the same evidence and how confident predictions challenge many expectations.

Ben Shapiro

Ben Shapiro (born January 15, 1984) is an American conservative political commentator and media host, best known for his aptly named political podcast The Ben Shapiro Show and media company The Daily Wire. Shapiro describes his political views as economically libertarian and socially conservative, while staying critical of the alt-right movement. Before becoming a political commentator, Shapiro studied political science at the University of California before attending Harvard Law School. 

Serving as the host of The Ben Shapiro Show, Shapiro provides commentary and coverage of current events, cultural issues, daily news, and political commentary. Episodes can be watched on YouTube and listened to on Spotify, Apple Podcasts, and The Daily Wire, each featuring top news stories and occasional guest interviews.

Shapiro co-founded The Daily Wire, an American conservative news and media company, in 2015. Similar to his personal show, the company offers a right-wing perspective on trending topics, trends, cultures, and global affairs through articles, opinion pieces, and daily reporting.

Fans often tune in to Shapiro's show because of his rapid-fire delivery, ability to articulate conservative viewpoints aggressively, and his perceived intellect. Many individuals view him as effective at defending conservative principles with facts and logic and enjoy his confrontations with political opponents and liberal media narratives. 

When looking at the 2024 presidential election, we can see how Shapiro's coverage presented the election from a strongly conservative perspective, which influenced his predictions. On Election Day, Shapiro posted a video titled "ELECTION DAY!! My Prediction and More," where he discussed, at length, the available evidence and gave his predictions for how the night would unfold. Rather than simply reporting results, he considered all indicators of elections.

Shapiro's analysis was heavily influenced by his conservative political perspective. He was generally supportive of Donald Trump and critical of Kamala Harris and the Democratic Party, which affected the issues he emphasized when discussing the election. Rather than treating the outcome as completely unknowable, his Election Day commentary attempted to interpret the available evidence and explain what he expected to happen: Trump's victory as certain. This is indicative to predictive journalism because he is using real evidence while still allowing his political perspective to influence which evidence receives the most attention. His prediction also demonstrates the uncertainty involved in elections––even a confident forecast is different from knowing the outcome with certainty.

Rachel Maddow

Rachel Maddow (born April 1, 1973) is an American television news program host and liberal political commentator. She is best known for her aptly named weekly television show on MS NOW (formerly known as MSNBC), The Rachel Maddow Show, multiple Emmy awards for her broadcasting work, and is the first openly lesbian anchor to host a major prime-time news program in the United States. Before becoming a political commentator, Maddow attended Stanford University, where she received a bachelor's degree in public policy, and later received her doctorate in political science at Oxford University.

Maddow has written a multitude of novels covering American politics and has launched multiple podcasts centered around political scandals and affairs. Her most notable one, however, is The Rachel Maddow Show. Maddow provides an in-depth analysis of major political stories, investigative reporting, and interviews with newsmakers. 

Maddow's show premiered in 2008 as an echo of her former talk show program of the same name on Air America Radio. The program offers a left-leaning perspective on political media and is known for its deep dives into political history, mechanics, and transparent storytelling. Episodes can be found on the MS NOW website, listened to on Apple Podcasts, Spotify, and YouTube, each featuring a narrative style that connects complex political dots and interviews with politicians, journalists, and key figures of the current event being covered. 

Fans tune in to Maddow because of her detailed storytelling, deep and expansive historical context, and engaging, liberal-leaning perspective on political events. To many audiences, her narrative style feels more like a documentary rather than a history lesson, where she breaks down complex political issues by connecting them to lesser-known historical events. 

Maddow's coverage of the 2024 presidential election provides a stark contrast of how political commentators can interpret the same evidence differently. Her coverage frequently focused on the potential consequences of Trump's victory for American democracy, presidential power, elections, and political institutions. Rather than focusing primarily on the possibility of a Republican victory as a political realignment, Maddow examined what a Trump presidency could mean for the country. 

One example of her coverage came shortly after Election Day, when Maddow discussed a Des Moines Register poll that showed Harris leading Trump in Iowa. Maddow noted that if the poll was accurate, the results could have implications beyond the state. But the poll ultimately proved inaccurate, and Trump won Iowa by a substantial margin. This example demonstrates one of the challenges of predictive journalism: even a poll can produce a prediction that doesn't reflect the final result. 

Maddow's coverage also demonstrates that predictions aren't always about who will win an election, but what might come after. After Trump's victory, she emphasized his past statements and actions and commented on her concerns about his approach to political power and the possible effects of another Trump administration on certain issues. 

Her coverage tended to frame the election not only as a contest between the two candidates and their policies, but also as a significant choice about the future of American democracy and government institutions. 

Her and Shapiro's coverages demonstrate two different approaches to political prediction. Shapiro focused more directly on interpreting the evidence to anticipate the election's outcome, while Maddow focused on the possible political and institutional consequences of that outcome. Neither approach is the same as knowing the future with certainty, which is why audiences should distinguish between evidence-based forecasting, interpretation, and political commentary.

What We Learn from Predictive Journalism

Predictive journalism isn't always harmful, especially when audiences are aware of what political bias may be driving an assumption. This type of coverage encourages conversation and gives audiences an overview of what could happen in an event. While audiences don't necessarily learn who will win an election, they do gain an insight into what experts believe is most important about an election and on what premise they're basing this assumption.

Being wrong doesn't necessarily mean a journalist was irresponsible because elections are uncertain events with multiple variables that could easily change the tide. A candidate may have an 80 percent chance at winning, but they also have a 20 percent chance at losing. The problem with predictive journalism is when audiences interpret a probability as a guarantee––and political news media encourage this behavior because definitive statements are more interesting and engaging than uncertainty. 

Predictive journalism is useful when it teaches audiences how to think about outcomes and understand the future rather than pretending to know these things. Polls, commentators, forecasts, and experts can all be wrong, and understanding these limits and the evidence surrounding a political event teaches audiences to not only live in comfort, but expect the unexpected.