The emergence of 3D-printed firearms: An analysis of media and law enforcement reports
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
3D-printed firearms, an emerging category of privately made firearms (PMF) produced beyond government control, have become increasingly prevalent due to technological advancements. They are now emerging as a cost-effective and reliable alternative to conventional firearms. Raised to public awareness following the 2013 release of the 3D-printed Liberator, these firearms are now more commonly encountered by police forces. This article analyses various reports involving 3D-printed firearms, reflecting the increasing encounters by law enforcement agencies. It examines 186 cases involving 3D-printed firearms, primarily from North America, Europe, and Oceania, highlighting a significant rise in incidents since 2021. These incidents include seizures, illicit uses, and online sales, with the firearms typically being hybrid models, Parts Kit Completions/Conversions (PKC), or firearm components such as auto sears. The study underscores the use of affordable equipment and materials for production, emphasizing the accessibility and potential risks of these firearms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it