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
The notion of culture implies the relative stability of sets of algorithms that become entrenched in human brains as children become socialized, and, to a lesser extent, when immigrants become assimilated into a new society. The semiotics of culture has used the notion of signs and systems of signs to conceptualize this process, which takes for granted memory as a natural affordance of the brain without raising the question of how and why cultural signs impact behaviour in a durable manner. Indeed, under the influence of structuralism, the semiotics of culture has mostly achieved synchronic descriptions. Dynamic models have been proposed to account for the action of signs (e.g., semiosis, dialogism, dialectic) and their resulting cultural changes and cultural diversity. However, these models have remained remarkably abstract, and somewhat disconnected from the actual brain processes, which must be assumed to be involved in the emergence, maintenance, and transformations of cultures. Semiotic terminology has contributed to a systematic representation of cultural objects and processes but the philosophical origin of its basic concepts has made it difficult to construct a productive interface with the cognitive neurosciences as they have developed and achieved notable advances in the understanding of memory over the last few decades. The purpose of this paper is to suggest that further advances in semiotics will require a shift from philosophical and linguistic notions toward biological and evolutionary models.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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