Consciousness as an intelligent complex adaptive system: A neuroanthropological perspective
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.017 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".