Unconscious perception and central coordinating agency
Bibliographic record
Abstract
Abstract One necessary condition on any adequate account of perception is clarity regarding whether unconscious perception exists. The issue is complicated, and the debate is growing in both philosophy and science. In this paper we consider the case for unconscious perception, offering three primary achievements. First, we offer a discussion of the underspecified notion of central coordinating agency, a notion that is critical for arguments that purportedly perceptual states are not attributable to the individual, and thus not genuinely perceptual. We develop an explication of what it is for a representational state to be available to central coordinating agency for guidance of behavior. Second, drawing on this explication, we place a more careful understanding of the attributability of a state to the individual in the context of a range of empirical work on vision-for-action, saccades, and skilled typing. The results place pressure on the skeptic about unconscious perception. Third, reflecting upon broader philosophical themes running through debates about unconscious perception, we highlight how our discussion places pressure on the view that perception is a manifest kind, rather than a natural kind. In doing so, we resist the tempting complaint that the debate about unconscious perception is merely verbal.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.015 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".