Bibliographic record
Abstract
In The Other Wild West, the author discusses the revisionist arguments on American Old West violence as put forward by leading historians including Robert Dykstra and Lynn Perrigo, systematically debunking former work by Roger McGrath and Ray Billington on cow-town violence. Drawing on Richard Brown’s argument that Old West violence was a part of the same conflict as the Indian Wars, the author demonstrates how violence in this era was neither reduced to individual vigilantism nor white-on-white aggression. The author concludes that although conflicts were more collective, systematic and transnational than conventional understandings suggest, the myth of personal violence persists. The author discusses the value that this myth has played in forming national consciousness and bolstering political rhetoric and how this has tangled the historical credence of pop-culture with documented reality. The author holds that such confusion dispossesses non-white participants from the historical purview; those who not only played formative roles but were themselves also victims of the most violence. Because of the disinheritance intrinsic to the old west myth of personal violence, the author forwards a continual re-visitation of de-facto history.
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 | 0.001 | 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 | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".