The <i>longue durée</i> of the Human Terrain: Politics, cultural knowledge and the technical fix
Bibliographic record
Abstract
The recent end of the Human Terrain System run by the US Army has brought to a close one of the most recent insidious challenges to the field of anthropology. But while the anthropological elements of the programme have been well documented, and contested, its historical roots have not. The HTS and cultural knowledge apparatus of the American defence establishment draw deeply upon the wells of British scholar administrators of the nineteenth century. Of particular importance, especially in regard to Afghanistan, is Mountstuart Elphinstone who published the foundational text about the country, An account of the Kingdom of Kabul , 200 years ago. But unlike the HTS and similar programmes run by other Western governments which treat culture as a kind of technical aspect of governance, Elphinstone appreciated the importance ‐ and legitimacy ‐ of local politics.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.090 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| 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".