Armed Citizens on the Border: How Guns Fuel Anti-Immigration Politics in America
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 To make a nation on stolen land using enslaved labor, the early American state relied on gun and immigration policy to create a well-armed white settler population. This legacy continues to animate modern conservativism, which is staked on supporting gun-friendly and anti-immigrant policies. Despite this history and ongoing political reality, however, the sociology of migration has largely ignored the relationship between firearms and immigration politics. To explore this relationship, the current study draws on 20 months of ethnographic data from the U.S.-Mexico border. I show how contemporary American gun culture bolsters anti-immigrant organizations through two mechanisms. First, gun shows and shooting ranges are important sites of recruitment among anti-immigrant groups. Second, the thrill of handling firearms mitigates the monotony of everyday anti-immigrant activism, while also easing the disenchantment that participants may otherwise feel about the effectiveness of their actions in bringing about long-term change. The article concludes by urging scholars of American politics to be mindful of the legacies of settler-colonialism and to take seriously the reinforcing effects of guns on nativist politics.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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 it