Consciousness as an intelligent complex adaptive system: A neuroanthropological perspective
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 In complexity theory, both the brain and consciousness are understood as trophic systems—they consume metabolic energy when they function. Complex systems are dynamic and nonlinear and comprise diverse entities that are interdependent and interconnected in such a way that information is shared and that entities adapt to one another. Some natural complex systems are complex adaptive systems (CAS), which are sensitive to change in relation to their environments and are often chaotic. Consciousness and the neural systems mediating consciousness may be modeled as CAS and, more specifically, as intelligent complex adaptive systems (ICAS), where intelligence means that a nervous system can solve problems successfully by intervening between sensory input and behavioral output. Evolution of any ICAS will result in emergent properties, particularly advanced brains. Two processes are involved in integrating experience and knowledge: the effort after meaning and the effort after truth. These efforts are mediated by the predominance given to direct experience presented to the brain's sensorium and modeling processes mediated by higher cognitive functions. Understanding consciousness as an ICAS has profound repercussions in how anthropology conceives of culture.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.015 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it