Bibliographic record
Abstract
The next chapter examines the punctuated life of Florinskii’s book in the late-Soviet and post-Soviet eras. In the early 1970s, Ivan Kanaev, a geneticist-turned-historian, published the first Russian language biography of Galton’s and an extensive analysis of Florinskii’s treatise. This time, however, Florinskii’s tract was presented as a foundational work not of eugenics, but of … medical genetics! References to Florinskii and his book began to appear in popular articles and introductions to the textbooks on the subject. But it took more than twenty years and the dissolution of the Soviet Union, until Florinskii’s treatise was reprinted again in 1995, through the efforts of Valerii Puzyrev, director of the Tomsk Institute of Medical Genetics. In 2012, the book was reissued once more, this time as the opening piece in a ‘reader on Russian eugenics,’ compiled by the self-styled ‘racial encyclopedist’ and ‘bio-politician’ Vladimir Avdeev. This chapter scrutinizes the renewed interest in Human Perfection and Degeneration and explores various factors that contributed to its long quiescence and inspired its new revival in late-Soviet and post-Soviet Russia.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".