War‐making and sense‐making: some technical reflections on an instance of ‘friendly fire’
Bibliographic record
Abstract
In this paper we analyse a 'friendly fire' incident from the second Gulf War and the controversy which came to envelop it during a coroner's inquest in 2007. Focusing on the cockpit video of the incident that was leaked to the media during that inquest, we examine what the military and civilian investigators were involved in reconstructing: the incident as it unfolded in real time. Our analysis is grounded in a praxeological perspective that draws on and links ethnomethodological studies of work, research into 'normal' accidents, disasters and risks, and recent ethnographies of the military. Based on our analysis, we suggest that the accounts offered after the event by the military and civilian inquiries should be treated less as competing descriptions than different ways of problematizing particular aspects of the military-political 'machineries' the pilots' actions were enmeshed within.
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 | 0.020 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.035 | 0.106 |
| Scholarly communication | 0.024 | 0.021 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".