Bibliographic record
Abstract
The Italian philosopher Giambattista Vico foreshadowed many of the ideas currently being entertained by the modem cognitive and human sciences. By emphasizing the role of the imagination in the production of meaning, Vico showed how truly ingenious the fIrst forms of representation were. His view that these forms were "poetic" is only now being given serious attention, as more and more linguists and psychologists come to realize the role of metaphor in the generation of abstract systems of representation. The Estonian semiotician Yuri Lotman espoused a basically similar view, highlighting the role of the poetic imagination in the generation of the textuality that holds cultures together in meaningful ways. A comparison of these two exceptional thinkers has never been entertained. This note aims to do exactly that. Specifically, it takes a first glimpse at the parallels of thought and method that inhere in the main works of these two ground-breaking thinkers. Such a comparison will establish a theoretical framework to make semiotics a true "science of the imagination". It will show that semiosis and representation are not tied to any innate neural mechanisms, but rather to a creative tendency in the human species to literally "invent itself'.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".