Between natural science and ethnography: On the relationship between the biological, ethnic and social
Bibliographic record
Abstract
Correlation between the biological, ethnic and social has been of historical importance to L. N. Gumilev’s passionarity theory of ethnogenesis and remains so today. Modern ethnography, including at Saint Petersburg State University, continues to misunderstand the essence of this part of the Gumilev paradigm while attempting to form a pseudo-loyal attitude to Gumilev’s legacy. This pseudo-loyalty is well demonstrated by ethnographers’ thesis about the equivalence of civilisation and super-ethnos according to Gumilev, whereas civilisation is actually only a temporary social shell of super-ethnos. This paper shows that modern ethnographers and culturologists essentially stay beyond the scientific (naturalistic) approach to ethnogenesis introduced and defended by Gumilev. It therefore discusses the possibility of developing a consistent view of the relationship between the biological, ethnic and social based on the concepts of cooperative human behaviour put forward by synergetics. This perspective taps into Gumilev’s understanding of the nature of the ethnic system as a local case of synergetic adaptation to the environment through cooperative behaviour. We argue for viewing cooperative human behaviour as a strange attractor responsible for the transfer of matter, energy and information between three divergent levels of structural organisation. This view specifically explains the periodic discrepancies between the harsh social conditions of civilisation and the high level of culture it is able to maintain. Given this as a basis, Gumilev’s theory of ethnogenesis should be primarily seen and used as an external tool applied in culturology. As such, it can contribute to the development of a modern synergetic paradigm for culturology.
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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 | 0.021 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.006 | 0.110 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".