Grounding Knowledge/Walking Land: Archaeological Research and Ethno-Historical Identity in Central Nepal
Bibliographic record
Abstract
Tracking knowledge down to ground — concerned with trail-based archaeology, journeys and histories, this is a volume of both ‘firsts’ and ‘thick context’. Atface-value it documents almost a decade of ground-breaking investigations within the Annapurna highlands of Nepal. Including survey recording of fort and settlement sites, from the outset the project’s focus was the extraordinary ruins of Kohla Sombre — Kohla, The Three Villages — the ancestral settlement of the Tami-mai (Gurung) community, who hosted and instigated the fieldwork programme. Ultimately, only a single season’s excavation was conducted, before the project was cut short by the political insurgency within the country. It concluded with holding a great shamans’ meeting in Pokhara in 2002, at which their historical ‘oral texts’ were presented. Narrating the long migration of the Tamu-mai into the region and down from a distant north, the present volume includes the full translation of one of these oral epics, the Lẽmakõ Rõh Pye. The project represents a unique collaboration between archaeologists, anthropologists and a shaman. Including interviews with upland inhabitants, the volume encompasses the diverse voices of both its immediate participants and the local community. Fulsome in its presentation of the archaeological data and rich in ethnographic source-material, not only is this book crucial for Himalayan culture studies generally, but also relevant for any concerned with the construction and context of the past in the present, and the active forging of ethno-historical identities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".