THE 1926/27 SOVIET POLAR CENSUS EXPEDITIONS
Bibliographic record
Abstract
In 1926/27 the Soviet Central Statistical Administration initiated several yearlong expeditions to gather primary data on the whereabouts, economy and living conditions of all rural peoples living in the Arctic and sub-Arctic at the end of the Russian civil war. Due partly to the enthusiasm of local geographers and ethnographers, the Polar Census grew into a massive ethnological exercise, gathering not only basic demographic and economic data on every household but also a rich archive of photographs, maps, kinship charts, narrative transcripts and museum artifacts. To this day, it remains one of the most comprehensive surveys of a rural population anywhere. The contributors to this volume – all noted scholars in their region – have conducted long-term fieldwork with the descendants of the people surveyed in 1926/27. This volume is the culmination of eight years’ work with the primary record cards and was supported by a number of national scholarly funding agencies in the UK, Canada and Norway. It is a unique historical, ethnographical analysis and of immense value to scholars familiar with these communities’ contemporary cultural dynamics and legacy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".