Bibliographic record
Abstract
In the Western word, the study of ideographic writings is often impaired by a kind of terminological confusion which is more due to theoretical negligence than to insufficiency in practical knowledge of ideographic languages. In this article, we try to dispel this confusion by examining its origin. Through the examination, we shall make distinction between logogram and ideogram ; the question “when drawing become writing” is to be answered. The classification of ideograms will also be under consideration anew. The last part of this article will be devoted to the distinction between alphabetic systems and ideographic systems. Key words: ideogram; logogram; pictogram; drawing; alphabet; study of writing Resume: En Occident, l’etude des systemes d’ecriture ideographiques s’accompagne souvent d’une confusion terminologique qui est due plus a une negligence theorique qu’a une insuffisance de connaissances en langues qu’on dit en general ideographiques. Dans le present article, nous essayons de dissiper cette confusion en menant des reflexions sur son origine, au fil desquelles nous serons naturellement oblige de faire le depart entre logogramme et ideogramme, nous repondrons a la question quand un dessin devient signe d’ecriture. Nous reexaminerons egalement la classification des ideogrammes; pour ce faire, nous mettrons a contribution des approches semiologiques. La derniere partie de l’article sera consacree a une comparaison entre systeme ideographique et systeme alphabetique; a la suite de la comparaison on saura pourquoi l’ecriture n’a pas evolue vers l’alphabet. Mots cles: ideogramme; logogramme; pictogramme; dessin; alphabet; grammatologie
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".