Scaling up from sentience: modularity, conscious broadcast, and a constitutive solution to the combination problem
Bibliographic record
Abstract
Complexity in biology typically has less complex evolutionary antecedents which, for consciousness, begs the question of how a fully elaborated and unified consciousness, as we experience it, would have been scaled up from what we can assume to have been simpler, or at least different, beginnings. This poses difficulties for some theories, but is much simplified if the contents of consciousness combine in a constitutive way, so the balance between contents can be adjusted by natural selection incrementally as required, across generations, in evolutionary time. This contrasts with theories postulating an integrative solution to the combination problem, and is easiest to conceptualize by supposing that conscious sensations arise from the action of modular entities, each of which, regardless of spatial location, contributes separately to the total experience. There are, in consequence, two very different models for consciousness: that it is (1) non-modular, non-local and fully integrated at a conscious level, the more conventional view, or (2) modular, local, and constitutive, so that integrative processes operating at scale are carried out largely if not exclusively in a non-conscious mode. For a modular/constitutive model that depends on a broadcast mechanism employing a signal, what may be most important is the amplitude of the signal at its source rather than how far it is propagated, in which case each module must be structured so its output has precisely controlled characteristics and adequate amplitude. A model based on signal amplitude rather than propagation over distance would still require that conscious sensations adapted to serve memory accompany cognitive functions over which they exert only indirect control, including language and thought, but fails to explain how a localized signal comes to be perceived as pervasive and global in character. In contrast, the problem with integrative models is the assumption that consciousness acts globally and only globally, which risks misdirecting attention, both in theory and experiment, to anatomical structures and neurophysiological processes that may have little to do with the processes by which conscious sensations are produced or how brains come to be aware of them.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.004 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".