Bibliographic record
Abstract
Selected by Choice as an Outstanding Academic Title for 2003 The word “violence” conjures up images of terrorism, bombings, and lynchings. Beaten Down is concerned with more prosaic acts of physical force—a husband slapping his wife, a parent taking a birch branch to a child, a pair of drunken friends squaring off to establish who was the “better man.” David Peterson del Mar accounts for the social relations of power that lie behind this intimate form of violence, this “white noise” that has always been with us, humming quietly between more explosive acts of violence. Broad in its chronological and cultural sweep, Beaten Down examines interpersonal violence in Washington, Oregon, and British Columbia beginning with Native American cultures before colonization and continuing into the mid-twentieth century. It contrasts the disparate ways of practicing and punishing interpersonal violence on each side of the U.S.-Canadian border. Del Mar concludes that we cannot comprehend the causes and moral consequences of a violent act without considering larger social relations of power, whether between colonizers and original inhabitants, between spouses, between parents and children, or between and among different ethnic groups. The author has drawn on a vast array of vivid sources, including newspaper accounts, autobiographies, novels, oral histories, historical and ethnographic publications, and hundreds of detailed court cases to account for not only the relative frequency of different forms of violence, but also the shifting definitions and perceptions of what constitutes violence. This is a thoughtful and probing account of how and why people have hit each other and the manner in which opinion makers and ordinary citizens have censured, defended, or celebrated such acts. Del Mar’s conclusions have important implications for an understanding of violence and perceptions of violence in contemporary society.
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.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.864 | 0.770 |
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".