In this article, we want to provide a summary of our book’s core argument and draw out its implications for Trump’s second term as well as for the years after Trump leaves center stage.

We obtain point identification and propose a debiased machine learning estimator, derive its asymptotic distribution, and show how this can be used to carry out inference for the FA-frontier.

Added insights from models more precisely illustrate just what kind of balance between minority rights and majority rule the reform would strike, but in others, they show that the reform could backfire on members of the majority or on the reformers who want the Senate to spend less time wrangling with obstruction.

A first-of-its-kind national research resource that links nearly 23,000 U.S. public high schools to the economic, educational, health, housing, and crime conditions of the communities they serve.

Social cognitions could play an important role in violence and may be modifiable through intervention.

By prioritizing robust reforms to our existing unemployment and workforce systems that benefit all workers — not just those who can prove that their jobs were eliminated due to AI — Congress can help the U.S. workforce retool without repeating the mistakes of TAA.

Limited consideration is indispensable for credible inference and welfare analysis of choice under risk in field environments.

While LLMs should be kept well clear of formal democratic decision-making processes, we think they can instead strengthen the informal public sphere—the arena that mediates between democratic governments and the polities that they serve, in which political communities seek information, form civic publics, and hold their leaders to account.

The period of problem solving in criminal justice appears to be over, driven by increasing public concern about crime and repolarization in response to social movement activism.