‘We who move’: the built environment of nomads in the Suleiman Mountains of Balochistan, Pakistan
Bibliographic record
Abstract
Abstract This paper looks at nomad pastoralists migrating back and forth through the Suleiman Mountains of northern Balochistan, as part of their annual movements and importantly as guides for historic caravans. These caravans brought trade goods, particularly Central Asian horses, from the west to India. This ‘Silk Road’ link is central to the Karez System Cultural Landscape World Heritage nomination. Due to limitations on funding, challenges of physical access, politics and local conflicts, much of the research on these historic nomad movements and their built environment has been carried out using remote sensing imagery. It is possible to follow their trails marked in the images by compacted pathways, campsites, corrals, trail-side cemeteries and soil discolourations. This transient heritage is critically threatened as these nomad groups have been refused entry into Pakistan from Afghanistan due to border closures and conflict. The imagery over time shows how the nomadic built environment is becoming a layer of archaeological deposits. The most interesting challenge is how can this kind of ‘minimal heritage’ be documented, conserved and managed and whether it is possible to design a methodology for its preservation in some form.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".