Theoretical Reflections on the Possible Causes of Egalitarian Syndrome Inertia
Bibliographic record
Abstract
Jedna od osnovnih postavki teorije egalitarnog sindroma Josipa Županova, postavka o egalitarnom sindromu kao klasteru naslijeđenih neformalnih normi, kompatibilna je s nekoliko teorijskih koncepata kulturne inercije.Iz perspektive teorija ovisnosti o prijeđenom putu perzistencija egalitarnog sindroma može se objasniti djelovanjem faktora odgovornih za reprodukciju društvenih normi.Riječ je o faktorima koji ne utječu na genezu određenoga društvenog fenomena (primjerice, normi), nego ga kroz vrijeme reproduciraju.Shodno rezultatima recentnih empirijskih istraživanja, jedan od reprodukcijskih faktora egalitarnog sindroma može se pronaći u tranzicijskim troškovima.Na osnovi toga, kao i propozicije o razlikovanju generativnih od reprodukcijskih faktora društvenih fenomena, legitimiramo tezu da tranzicijski troškovi nisu stvorili egalitarni sindrom, nego su pridonijeli njegovoj perzistenciji i u postsocijalističkom društvenom kontekstu.Moguće izvore hipoteza o dodatnim čimbenicima reprodukcije egalitarnog sindroma u tranzicijskim okolnostima pruža koncept kulturne inercije svojstven teorijskoj perspektivi institucionalizma, teorija kulturne evolucije Roberta Boyda i Petera J. Richersona, kao i koncept zapinjača Michaela Tomasella.Također, sukladno ideji o »efektu tunela« Alberta Hirschmana, možemo pretpostaviti da je očekivana stagnacija u društvenoj pokretljivosti jedan od mogućih specifičnih faktora reprodukcije egalitarnog sindroma. Ključne riječi:
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.046 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".