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Record W4382797153 · doi:10.31234/osf.io/rjn3k

Expectancies and the generation of perceptual experience: Predictive processing and phenomenological control

2023· preprint· en· W4382797153 on OpenAlexaff
Peter Lush, Zoltán Dienes, Anil K. Seth

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsCanadian Institute for Advanced Research
Fundersnot available
KeywordsPsychologyHypnosisCognitive psychologyContext (archaeology)PerceptionVolition (linguistics)Interpretative phenomenological analysisExpectancy theoryControl (management)Phenomenology (philosophy)Social psychologyEpistemologyQualitative researchComputer science

Abstract

fetched live from OpenAlex

Phenomenological control is the stable trait ability to alter subjective experience in accordance with goals. Although voluntary, phenomenological control is experienced as involuntary and has predominantly been studied within the context of hypnosis, in which direct verbal imaginative suggestions for a range of experiences are given by a designated ‘hypnotist’ (e.g., involuntary movement, paralysis, analgesia, amnesia or auditory, gustatory, tactile and visual hallucinations). However, hypnosis is not required for phenomenological control and the ability can be exercised in a variety of contexts, including in response to demand characteristics in scientific experiments. Here we trace the modern history of phenomenological control from the context of mesmerism in 18th century (which employed indirect, non-verbal suggestion) through to contemporary accounts. We focus on three theories: response expectancy theory (in which experience arises directly from expectancies), cold control theory (in which voluntary acts are experienced as involuntary due to being unaware of relevant intentions) and the predictive processing theory of hypnosis (in which voluntary acts arise from aberrant interplay of top-down predictions and bottom-up prediction error signals). We consider the pros and cons of each and explore the extent to which predictive processing might be extended to offer a full-fledged theory of phenomenological control.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.105
GPT teacher head0.300
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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