Bibliographic record
Abstract
The question of the origin of language is difficult to answer since language is involved in a complex way in all human activities. Yet it can be answered if we concentrate on the design properties of the linguistic sign and how they relate to recently discovered properties that are unique to the human brain. Human language is the result of a cascade of consequences from a suite of minute neurological changes that give some human neuronal systems a new “representational” capacity. These changes make sense in evolution, and there is empirical evidence for them. These uniquely human systems of neurons have the capacity to operate offline for input as well as output (Hurley 2008): they can be triggered not only by external events stimulating our perceptual systems but also by brain-internal events; they can also be activated while inhibiting output to any external (motoric) system. These Offline Brain Systems are not specifically designed for language but they provide the crucial property that made it possible for further innovations to occur that led to language; they coincidentally allowed mental states corresponding to elements of the perceptual and conceptual substances of language to meet in our brains to form Saussurean signs. Recursivity derives from the self-organization triggered by the chaotic system that emerged, and required no innovation in the human lineage. Keywords: Offline neuronal systems; Saussurean signs; self-organization; recursivity
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".