Bibliographic record
Abstract
George Hume&s;s account of his thirty-five years in Russia is exceptionally interesting. To Russia, however, it was a great boon; it had certainly left her temporarily humiliated, but her unexpectedly gallant defence had gained for her the respect and sympathy, not only of late enemies but of all civilised communities. Hume, writing his book thirty-five years later, tells the subsequent history of the Mennonites. When, in 1870, Russia introduced universal military conscription, vast numbers of Mennonites emigrated to Canada, the USA and Holland. Living as he did amongst the peasants, farming with them the black earth of southern Russia, Hume became intimately aware of the precariousness of their lives. One year out of three, he writes, some parts of Russia are in a state of semi-starvation. He felt that lack of schooling was at the root of many of Russia&s;s troubles. Russia had so many different nationalities, so many different climates and customs, he observed, that centralization was an anachronism.
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.
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 | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".