When wild war’s deadly blast was blawn: update on UK’s and other military fatality rates, and casualties, in Iraq and Afghanistan
Bibliographic record
Abstract
This commentary is a six-month update on UK military fatality rates per 1000 personnel-years in Iraq1, together with an account for Afghanistan for both UK and other forces. In 2006, there have been 32 UK military deaths in Afghanistan and 19 in Iraq where more than twice as many UK troops are stationed as in Helmand province, Afghanistan. Over 10,000 Afghan, British, Canadian and American troops are reported to be deployed on Operation Mountain Thrust in Afghanistan2. Military casualties, in addition to fatalities, are reported for both US and Canadian troops3 4. Blank columns signify that UK’s non-fatal military casualties in Iraq and Afghanistan (specifically: those who do not return to duty within 72 hours, as cited in the Edinburgh Fringe’s highly-acclaimed play, ‘Black Watch’) are still1 not properly collated, analysed and published. UK’s performance monitoring in the public services5 requires better if we are to discharge the debt of honour that parliament and public owe to our military forces. Analysis should properly take into account that military fatalities, and indeed casualties, may occur in clusters as when a helicopter or plane crashes, as occurred on 2 September 2006 when a Kinloss-based Nimrod came down in southern Afghanistan with the loss of 14 British lives, or there is a suicide bombing, or ordinance explodes. Deaths and casualty also dog those who have returned home, but are haunted by operations; and they add to the wages of war6-9. UK’s military fatality rate at the outset of operations in Helmand province in Afghanistan is comparable with the initial period of major combat in Iraq. Ten out of 11 deaths in Helmand to 12 August 2006 were hostile, whereas only two were of the preceding period’s (and locations’) seven, which included at least one each of accidental weapon discharge, suicide, homicide, and vehicle accident; and, additionally, there has been one non-hostile death due to vehicle accident on 11 August 2006 in camp at Kabul.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".