Bibliographic record
Abstract
This article considers translation as a factor in the genesis of social macro-formations—ethnoses and superethnoses. The research combines Niklas Luhmann’s social systems theory, Lem Gumilev’s theory of ethnogenesis and the concept of teleonomy borrowed from evolutionary biologist Ernst Mayr in order to demonstrate the ethnogenetic function of translation. An ethnos is a closed loose system; it has a life cycle which is teleonomic by nature. Ethnoses evolve by passing through different stages—from inception to consummation at the acmetic phase and finally into the post-acmetic succession of phases leading to disintegration. At each of these different stages, the social system requires inputs of varying intensity from the environment. Translation as a boundary phenomenon serves as a mechanism to ensure such inputs. From the standpoint of its social function, translation is theorized in a broader sense than usual—as mediation on intrapersonal, interpersonal, interethnic and intergenerational levels.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.036 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".