<p>Diagrammatic thinking: Notes on Peirce’s semiotics and epistemology</p>
Bibliographic record
Abstract
In this paper, I discuss the role of diagrammatic thinking within the larger context of cognitive activity as framed by Peirce’s semiotic theory of and its underpinning realistic ontology. After a short overview of Kant’s scepticism in its historical context, I examine Peirce’s attempt to rescue perception as a way to reconceptualize the Kantian “manifold of senses”. I argue that Peirce’s redemption of perception led him to a series of problems that are as fundamental as those that Kant encountered. I contend that the understanding of the difficulties of Peirce’s epistemology allows us to better grasp the limits and possibilities of diagrammatic thinking. Pensamiento diagramático: notas sobre la semiótica y la epistemología de Peirce En este artículo se discute el papel que desempeña el concepto de pensamiento diagramático en el contexto de la actividad cognitiva, tal y como es concebida dentro del marco de la teoría semiótica de Peirce y su subyacente ontología realista. Luego de presentar una visión general del escepticismo kantiano en su contexto histórico, se examina el esfuerzo de Peirce por rescatar la percepción, esfuerzo que lo lleva a indagar de manera innovadora el “multiespacio de los sentidos” del que hablaba Kant. Se mantiene que este esfuerzo lleva a Peirce a una serie de problemas que son tan fundamentales como los que Kant encontró en su propio itinerario epistemológico. Se sostiene que la comprensión de las dificultades intrínsecas a la epistemología de Peirce nos permite cernir mejor los límites y posibilidades de su pensamiento diagramático.Handle: http://hdl.handle.net/10481/4217Nº de citas en WOS (2017): 4 (Citas de 2º orden, 10)Nº de citas en SCOPUS (2017): 2 (Citas de 2º orden, 10)
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.034 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".