Symbol grounding and the origin of language
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
Organisms’ adaptive success depends on being able to do the right thing with the right kind of thing. This is categorization. Most species can learn categories (1) by direct experience (“induction”). Only human beings can learn categories (2) by word of mouth (“instruction”). Artificial-life simulations have shown the evolutionary advantage of instruction over induction and human electrophysiology experiments have shown that these two radically different ways of acquiring categories still share some common features in our brains today. Graph-theoretic analyses reveal that dictionaries consist of a core of more concrete words that are learned earlier, by direct experience (induction); the meanings of the rest of the dictionary can be learned by definition (instruction) alone, by combining the inductively grounded core words into subject/predicate propositions with truth values. We conjecture that language began when attempts to communicate through miming became conventionalized into arbitrary sequences of shared, increasingly arbitrary category names that made it possible for members of our species to transmit new categories to one another by defining and describing them via propositions (instruction).
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) | 0.001 | 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) | 0.000 | 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