Bibliographic record
Abstract
The paper summarizes six chapters of a book introducing Peircean visual semiotics to non-specialists. The book has an epistemological bent, and is intended as an empiricist response to Saussurean rationalism, locked away as it is in the universe of Thirdness. Inevitably, in reducing two hundred and thirty pages to twenty-four, the paper has been shorn of the majority of the original examples, quotations and summaries, the relations between the various chapters (here sections) are not developed in detail and the general presentation is perforce allusive: for example, the dynamic object, surely one of Peirce’s most potent yet least understood concepts, has been simplified in what is, after all, an introductory text; similarly, acquaintance with his system of categories has largely been taken for granted. Finally, Simonides of Ceos’ epigram stating that a poem is a talking painting and a painting a mute poem gives the book its title and a major leitmotiv, namely the way we obtain information from pictorial documents.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".