Public Mass Shootings: Counterfactual Trend Analysis of the Federal Assault Weapons Ban
Bibliographic record
Abstract
Background: Assault weapon and large-capacity magazine bans are potential tools for policy makers to prevent public mass shootings. However, the efficacy of these bans is a continual source of debate. In an earlier study, we estimated the impact of the Federal Assault Weapons Ban (FAWB) on the number of public mass shooting events in the United States. This study provides an updated assessment with 3 additional years of firearm surveillance data to characterize the longer-term effects. Objective: This study aims to estimate the impact of the FAWB on trends in public mass shootings from 1966 to 2022. Methods: We used linear regression to estimate the impact of the FAWB on the 4-year simple moving average of annual public mass shootings, defined by events with 4 or more deaths in 24 hours, not including the perpetrator. The study period spans 1966 to 2022. The model includes indicator variables for both the FAWB period (1995-2004) and the period after its removal (2005-2022). These indicators were interacted with a linear time trend. Estimates were controlled for the national homicide rate. After estimation, the model provided counterfactual estimates of public mass shootings if the FAWB was never imposed and if the FAWB remained in place. Results: The overall upward trajectory in the number of public mass shootings substantially fell while the FAWB was in place. These trends are specific to events in which the perpetrator used an assault weapon or large-capacity magazine. Point estimates suggest the FAWB prevented up to 5 public mass shootings while the ban was active. A continuation of the FAWB and large-capacity magazine ban would have prevented up to 38 public mass shootings, but the CIs become wider as time moves further away from the period of the FAWB. Conclusions: The FAWB, which included a ban on large-capacity magazines, was associated with fewer public mass shooting events, fatalities, and nonfatal gun injuries. Gun control legislation is an important public health tool in the prevention of public mass shootings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".