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Record W1980246637 · doi:10.3389/fnhum.2013.00469

Hypnosis as neurophenomenology

2013· article· en· W1980246637 on OpenAlexaff
Michael Lifshitz, Emma P. Cusumano, Amir Raz

Bibliographic record

VenueFrontiers in Human Neuroscience · 2013
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsJewish General HospitalMcGill UniversityMcGill University Health Centre
FundersUniversity of Oxford
KeywordsHypnosisPsychologyPsychotherapistMedicineAlternative medicine

Abstract

fetched live from OpenAlex

Hypnosis research binds phenomenology and neuroscience. Here we show how recent evidence probing the impact of hypnosis and suggestion can inform and advance a neurophenomenological approach. In contrast to meditative practices that involve lengthy and intensive training, hypnosis induces profound alterations in subjective experience following just a few words of suggestion. Individuals highly responsive to hypnosis can quickly and effortlessly manifest atypical conscious experiences as well as override deeply entrenched processes. These capacities open new avenues for suspending habitual modes of attention and achieving refined states of meta-awareness. Furthermore, hypnosis research sheds light on the effects of suggestion, expectation, and interpersonal factors beyond the narrow context of hypnotic procedures. Such knowledge may help to further foster phenomenological interviewing methods, improve experiential reports, and elucidate the mechanisms of contemplative practices. Incorporating hypnosis and suggestion into the broader landscape of neurophenomenology, therefore, would likely help bridge subjective experience and third-person approaches to the mind.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.025
GPT teacher head0.257
Teacher spread0.232 · 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 designBench or experimental
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

Citations28
Published2013
Admission routes1
Has abstractyes

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