Bibliographic record
Abstract
Abstract In the face of myriad crises in modern societies, semiotic inquiry has many valuable contributions to make. However, the long-standing dominant analytical paradigms in the field have made it exceedingly difficult, if not altogether impossible, to tackle the countless unanalyzable aspects of semiosis in the human condition. What needs to be done in semiotics is to highlight another mode of knowing, synthetic thinking, without excluding the analytical mode. Drawing inspiration and strength from classical Eastern philosophies and aesthetics, notably I Ching and Laozi , as well as classics and advances in global semiotics, the present paper proposes a cultural semiotics of jingshen , understood here as the holistic flux of mind, vitality, and creativity. This route of inquiry seeks cogent coalescence of the two foregoing modes of knowing so as to better inform semiotics in a new age. At the same time, it creates a unique methodology: the fusion of revelatory “embodied cognition” and “cognition via knowledge/ abstraction.” Viewed in this light, the purpose or function of semiotics is not limited to understanding signs and sign relations or uncovering laws governing the evolution of semiosis, but more importantly it embraces the improvement of mental capacity, the expansion of cognitive space, and the liberation of human thinking.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".