TRGETING SCIENCETrump’s War on Measurement Means Losing Data on Drug Use, Maternal Mortality, Climate Change and More
By slashing teams that gather critical data, the administration has left the federal government with no way of understanding if policies are working — and created a black hole of information whose consequences could ripple out for decades.
More children ages 1 to 4 die of drowning than any other cause of death. Nearly a quarter of adults received mental health treatment in 2023, an increase of 3.4 million from the prior year. The number of migrants from Mexico and northern Central American countries stopped by the U.S. Border Patrol was surpassed in 2022 by the number of migrants from other nations.
We know these things because the federal government collects, organizes and shares the data behind them. Every year, year after year, workers in agencies that many of us have never heard of have been amassing the statistics that undergird decision-making at all levels of government and inform the judgments of business leaders, school administrators and medical providers nationwide.
The survival of that data is now in doubt, as a result of the Department of Government Efficiency’s comprehensive assault on the federal bureaucracy.
Reaction to those cuts has focused understandably on the hundreds of thousands of civil servants who have lost their jobs or are on the verge of doing so and the harm that millions of people could suffer as a result of the shuttering of aid programs. Overlooked amid the turmoil is the fact that many of DOGE’s cuts have been targeted at a very specific aspect of the federal government: its collection and sharing of data. In agency after agency, the government is losing its capacity to measure how American society is functioning, making it much harder for elected officials or others to gauge the nature and scale of the problems we are facing and the effectiveness of solutions being deployed against them.
The data collection efforts that have been shut down or are at risk of being curtailed are staggering in their breadth. In some cases, datasets from past years now sit orphaned, their caretakers banished and their future uncertain; in others, past data has vanished for the time being, and it’s unclear if and when it will reappear. Here are just a few examples:
