Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.013 |
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 it