The Human Terrain System and Anthropology: A Review of Ongoing Public Debates
Bibliographic record
Abstract
ABSTRACT The advent of the U.S. Army's Human Terrain System (HTS) and the recruitment of anthropologists to provide “cultural knowledge” for the purpose of more effective counterinsurgency in Iraq and Afghanistan has created numerous conflicts and debates between HTS advocates and anthropological critics. These debates involve issues of ethical research, the role of anthropological research in war, the consequences of militarization, further harm to the reputation of the discipline, and the possible jeopardizing of anthropological fieldworkers who could be mistaken as U.S. spies. Those advocating for HTS claim that it is not unethical, that it helps to save lives, is not involved in collecting intelligence or targeting, and is a key way for anthropology to become relevant. This article serves as a primer on these debates and examines why HTS has largely failed to attract anthropological recruits.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.010 | 0.019 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".