Incident characteristics of fatal forcible entry warrant raids in the USA (2010–6)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Following the police killings of Breonna Taylor, Amir Locke, and others, forcible entry warrant raids (FEWRs) by law enforcement have become especially controversial in the USA. Despite the growing debate over this law enforcement practice, there is little available data, and consequently, a lack of empirical research related to FEWRs. The current study utilizes a nationwide public database of fatal FEWR incidents in the USA from 2010 to 2016 to examine nationwide trends of fatal FEWRs, civilian and officer characteristics, warrant characteristics, situational characteristics, and the outcomes of investigations and civil lawsuits following fatal FEWRs. Results suggest that, while fatal FEWRs were common between 2010 and 2016, Black and African American civilians were overrepresented in the data. Results suggest that fatal FEWRs most frequently occurred during the execution of drug warrants and about one-quarter resulted in the death of a civilian who was not armed with a firearm. Most of these cases resulted in no charges filed against the officers, but approximately one-quarter resulted in a civil lawsuit. This examination advances the limited research on FEWRs, providing greater detail on the common incident characteristics of these raids, along with the individuals and communities that are frequently impacted by them.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it