Bibliographic record
Abstract
Kelly Devries in “Catapults are not atomic bombs”—and in fact, of almost all of those who have joined the fray to, once and for all, kill off simplistic technological determinism—may have thrown out the baby with the bathwater. One aspect linking most of these anti-determinists is their temporal focus which is almost exclusively on pre-industrial revolutions in military technology. Furthermore, their views of the importance (or more accurately, the lack thereof) of technology in war is one that has ceased to apply to the world since the mid-nineteenth century. Technological determinism is not a disease of bad historical writing, but something that must be carefully applied in studying the technological systems of armed forces, regardless of time periods or geographic locations. We need to apply a definition of determinacy related to the systems theory that French writer Jacques Ellul proposed in The Technological Society . Here examples of military systems since the Industrial Revolution are covered and then this systems approach is applied to the pre-modern period. The approach moves us away from the radical assumptions of earlier determinists to show that technology is determinant, but only one of the many determinant factors that influence battles, campaigns, and wars. The study of military technology is central to any study of war, and we must not be afraid to move beyond a merely descriptive approach that appears to be promoted by the anti-determinists.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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; both teacher heads agree on what is shown here.
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".