Cultural Neurophenomenology: Integrating Experience, Culture and Reality Through Fisher Information
Bibliographic record
Abstract
Anthropologists and psychologists have long debated the relative importance of nature and nurture in human affairs. By and large anthropologists have opted for what might be called the ‘naïve culturological position’ that when our species developed culture, it left its biological roots behind. Psychologists, on the other hand, until relatively recently, have largely ignored the impact of culture upon the processes and functioning of the human mind. In their attempt to approximate the rigors of scientific methods practiced in the so-called ‘hard’ sciences, it is often a naïve scientism that drives theorizing and research in the discipline. The single most decisive impediment to the emergence of a mature anthropology and psychology is the mind–body schism. We will argue that bridging the mind–body schism requires a language by means of which we can refer to individual experience, culture and extramental reality simultaneously. Our approach is that of a cultural neurophenomenology that allows us to speak about the social and biological factors that produce, potentiate and limit human experience. We show that one key concept in unifying the languages of these different domains is ‘information’. We trace the history of the concept of information, and demonstrate that from the perspective of Fisher information one may more easily conceive of the interactions among experience, culture and reality in commensurable terms. Fisher information also allows us to model the relationship between knowledge and reality, and to suggest some of the mechanisms by which the individual psyche and a society's culture remain ‘trued-up’ relative to the reality of the world and the individual's own being.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.023 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.001 | 0.006 |
| 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".