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Record W2105847705 · doi:10.3389/fpsyg.2013.00894

Understanding egorrhea from cultural-clinical psychology

2013· article· en· W2105847705 on OpenAlexaff
Jun Sasaki, Kaori Wada, Yoshihiko Tanno

Bibliographic record

VenueFrontiers in Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyFeelingAnxietySocial anxietySocial psychologyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Based on his observations in Japanese clinical settings, Fujinawa (1972) conceptualized egorrhea syndrome, which includes symptoms such as erythrophobia, fear of eye-to-eye confrontation, olfactory reference syndrome, delusions of soliloquy, delusions of sleep talking, and thought broadcasting. The key feature of this syndrome is self-leakage, a perceived sense that one's personal internal information, such as feelings and thoughts, are leaking out. To reach a more comprehensive understanding of egorrhea, this paper aims to present general overview and reconsider the phenomenon of self-leakage using cultural-clinical psychology as a framework. First, the symptoms of egorrhea are reviewed in relation to other related psychopathologies such as social anxiety disorder (SAD) and taijin kyofusho (TKS), as well as schizophrenia. Second, a series of empirical studies conducted using Japanese non-clinical samples are summarized. The results of these studies form the basis for subsequent discussions, which incorporates the cultural-clinical psychology perspective proposed by Ryder et al. (2011). This paper ends with a general discussion regarding implications for research and clinical practice.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0020.016
Scholarly communication0.0050.006
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.244
GPT teacher head0.456
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2013
Admission routes1
Has abstractyes

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