Decades of fossil fuel influence paved way for Trump’s assault on university research, study says
Fossil fuel firms have spent years trying to regulate climate research by donating to US universities, study authors argue Recent attacks on US universities by the Trump administration have built on decades of efforts by libertarian donor networks, fossil fuel companies and conservative thinktanks to reshape university governance and increase outside influence, according to a new study. The…
A recent study published in PS: Political Science & Politics suggests that Republican members of Congress support Donald Trump's agenda due to shared voting patterns rather than fear. The research, conducted by Jeffrey M. Stonecash, an Emeritus Maxwell Professor at Syracuse University, indicates that a decades-long geographic realignment has aligned the party's presidential and congressional electoral bases.
In the American political system, the president is elected nationally while members of Congress are elected by specific states and districts, leading to a natural rivalry. However, over time, voting behavior has shifted, with voters increasingly choosing the same party for both presidential and congressional elections. This geographic sorting has resulted in local congressional districts mirroring national party lines.
Stonecash's analysis of election data from 1952 to 2024 reveals that Republican lawmakers back Trump because their local voters now share the same priorities as his national base, a situation not seen since 1952. The study maps how Republican presidential candidates began winning previously Democratic-leaning states as the party adopted more socially conservative platforms.
Trump currently enjoys a unique level of geographical overlap with his congressional party, with his congressional candidates winning in nearly every district he won in the presidential elections. This shared constituency explains the deference Congress shows to Trump, rather than intimidation.
Written by urgent.news from PsyPost's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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