Ranch Apocalypse: A Pataphysical Inquiry into the Mount Carmel Siege
Bibliographic record
Abstract
A total of 84 people were killed in the 1993 Bureau of Alcohol, Tobacco, and Firearms (ATF) raid on Mount Carmel in Waco, Texas. Debates continue about who was responsible—e.g., was it a government conspiracy or cultist militants intent on mass suicide? What hasn’t been fully considered, however, is the role the guns, tanks, toxic gases, and other “theater of war” accoutrements themselves played in the siege and resultant deadly inferno. Traditional metaphysical inquiries rest on the presupposition that the subject is separate from and sovereign over the object it examines. But as we have entered this intensely visual consumer culture, differences between subject and object disappear and the power of the subject collapses. Employing the postmodern metaphysics—here and elsewhere called “pataphysics”—of Jean Baudrillard to investigate this tragic battle, the author will argue that the ATF and the FBI were seduced by the compound’s castle and arsenal as well as their own. The helicopters, snipers, tanks, and CS gas turned what had begun on February 28, 1993, as a raid to serve a search warrant into a full scale military-style attack on a fortress and its peoples. Could it be that the federal agents became and were subordinate to the tools they were using?
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.023 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".