Peircean anti-psychologism and learning theory
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Taking influence from Peirce’s phenomenological categories (Firstness, Secondness, Thirdness), a notion of what we call bottom-up modeling has become increasingly significant in research areas interested in learning, cognition, and development. Here, following a particular reading of Peircean semiotics (cf. Deacon, Terrence. 1997. The symbolic species: The co-evolution of language and the brain . London and New York: W. W. Norton; Sebeok, Thomas and Marcel Danesi. 2000. The forms of meaning: Modelling systems theory and semiotic analysis . Berlin and New York: Mouton de Gruyter), modeling, and thus also learning, has mostly been thought of as ascending from simple, basic sign types to complex ones (iconic – indexical – symbolic; Firstness – Secondness – Thirdness). This constitutes the basis of most currently accepted (neo-Peircean) semiotic modeling theories and entails the further acceptance of an unexamined a priori coherence between complexity of cognition and complexity of signification. Following recent readings of Peirce’s post-1900 semiotic, we will present, in abbreviated form, a discussion as to the limits of this theoretical approach for theories of learning that draws upon Peirce’s late semiotic philosophy, in particular his late work on iconicity and propositions. We also explore the corollary conceptions of semiotic resources and competences and affordances to develop an ecological perspective on learning that notably does not impose a linear developmental progression from simple to complex. In conclusion, we address some of the implications of this (post-Peircean) conceptualization for transdisciplinary research into learning.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it