Inner Speech, Self-regulation and the Modular-with-Feedback-Theory of Free Will
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
This paper demonstrates a synergy between the Inner Speech model of free will and the Modular-with-Feedback Theory. The first section examines determinism and causation to argue that free will requires the ability of an agent to make a non-deterministic choice, which could have been decided otherwise. This in spite of physical, hereditary and environmental ad hoc factors which inevitably influence choice. Section two introduces the Modular-with-Feedback Theory which proposes free will to be compatible, not with determinism, but with chance. It provides a model of how free will emerges from oscillating neuronal activity in neural modules. These, representing ideas, oscillate subconsciously, competing for conscious attention. Although the choice between them is partly random the modules are able to maintain a sense of context and consistency, leading to a conscious desire for a sense of character. Learning from experience, we use feedback to rebalance. Conscious decisions, using inner speech, train the subconscious to advance, in the future, options better conforming to our desired will. Section three discusses how consciousness emerges non-deterministically in a manner consistent with a causally interactive dualism that is, at a hidden level, monist. Section four explains how inner speech self-regulates our behavior by talking us through free, usually consistent choices, conferring moral responsibility. Some abnormalities of inner speech diminishing free will are discussed, and further research programs proposed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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