Bibliographic record
Abstract
Abstract The present issue of Chinese Semiotic Studies is published in memory of Thomas A. Sebeok. Sebeok was not only a master semiotician, but more importantly a grand artist in semiotics. As one of the most important contemporary figures in semiotics, linguistics, ethnology, and cultural studies, Sebeok made profound contributions to the progress of global semiotics through his distinguished theoretical achievements and promotional activities. His works have proven to be so relevant that they continue to exert a determinative influence and provide directions for the development of semiotics and its many subdivisions, especially biosemiotics, beyond the 20th century. Now, 21 years into the present century, during which semiotic studies around the world have made remarkable progress, it is about time to highlight some specific ways in which his contributions will continue to shape and guide semiotic studies, demonstrating the relevance of these contributions to the 21st century challenges. To this end, this special issue presents some up-to-date and informed studies that explore Sebeok’s contributions to semiotics and their vital implications for fundamental problems relevant to humanity as a semiotic animal in the present day and in the rest of this century and beyond.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".