Alienation flows through the barrel of a gun: Despair, mass shootings, and suicide in an American settler colony
Bibliographic record
Abstract
In what is now referred to by many as the United States, gun violence rages on. When one considers the country’s sheer number of annual gun deaths, the data is as overwhelming as it is distressing. Indeed, perhaps the only thing outpacing the trauma and loss of life wrought by gun violence is the anguish and grief of those who are impacted by it. Despite the shocking statistics and fervent calls for change, few efforts have been effective at curbing the harm. Such a reality raises pressing questions about why gun violence in the U.S. is so prevalent, and what can be done to prevent it. In this Contention, I maintain that the only way out of the U.S.’s centuries-long doom spiral of gun violence will be reckoning with the nation’s historical-ongoing trajectories of settler colonialism, heteropatriarchy, white supremacy, and imperialism. I further contend that any effort to eliminate gun violence in the U.S. mandates ending mass alienation and taking masculinity to task. Accordingly, I illustrate how guns are not actually the root of the problem, even though their ease of access and the culture(s) surrounding them are corollary symptoms that necessitate urgent intervention. In short, I argue that resolving gun violence in the U.S. demands a historical-structural-intersectional focus and that the source of the country’s firearm-involved deaths are alienation, despair, and oppression owed to capitalism, entrenched patriarchal social relations, and the settler colonial state––all of which must be abolished if we are seriously concerned with livable futures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".