Bibliographic record
Abstract
The third chapter details the actual contents of Florinskii’s essays, tracing their major themes and ideas to a variety of English, French, German, and Russian sources, first and foremost, Darwin’s Origin. Florinskii applied Darwin’s key notions of variability, heredity, and selection to the understanding of the past history, the present state, and the possible future of humanity and examined how Darwin’s ‘laws of selection’ might play out in the evolution of the human species. Much like Galton’s, Florinskii’s major idea was based on Darwin’s analysis of different forms of selection (artificial, natural, and sexual) and on implicit analogies between artificial selection (the choice of progenitors in both its ‘unconscious’ and ‘methodical’ varieties) and sexual selection (the choice of mating partners). For Florinskii, these analogies were likely facilitated and amplified by a particular contemporary Russian translation of Darwin’s key term ‘selection’ as podbor rodichei (matching of kin) and vybor (choice), as well as by a popular equation of species evolution with ‘progress.’ The essence of Florinskii’s idea of ‘rational’ marriage was to replace the ‘unconscious’ choice of marital partners (‘masquerading as love,’ in Florinskii’s words) with a ‘rational’ one. In order to identify the sources and causes of degeneration and to discover the principles of perfection, Florinskii synthesized available data, ideas, and concepts from an array of scientific fields and medical specialties, from physical anthropology to social hygiene, general biology, and theoretical gynecology. In seeking to understand the ‘conditions conducive’ to perfection and degeneration, he also identified those characteristics—the ideals of human health, beauty, and mind—which together should guide a rational selection of spouses. Since he equated beauty with health and mind with the brain, ‘physical and moral health’ emerged as the key criteria of spousal choice in his concept of ‘hygienic’ marriage.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".