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Record W2085311148 · doi:10.7825/2164-6279.1546

Mysticism in Patañjali’s Yoga Sūtras and in Carl Jung’s Psychology

2013· article· en· W2085311148 on OpenAlexaff
Harold Coward

Bibliographic record

VenueJournal of Hindu-Christian studies · 2013
Typearticle
Languageen
FieldPsychology
TopicJungian Analytical Psychology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMysticismPhilosophyMeditationPsychoanalysisPsychologyTheology

Abstract

fetched live from OpenAlex

In this article we will examine the understandings of mysticism as offered by Patañjali’s Yoga Sūtras I:41-51 and Carl Jung’s Western psychology. For our purposes, mysticism is not to be understood as something “misty,” vague or emotional (to list but three current misinterpretations). Rather, as understood by the great mystics of all religious traditions, mysticism is experienced as something like sensory perception – only more direct and more vivid! In Patañjali’s Yoga, for example, mysticism is a case of intuition or supersensuous perception (pratibhā) from which distorting emotions have been purged by disciplined meditation. While Western philosophers such as Bertrand Russell have attempted to dismiss mysticism as merely subjective emotion, or the psychoanalyst Sigmund Freud as an “oceanic feeling,” Patañjali’s claim is just the opposite. According to his Yoga psychology, mystical experience is a case of the direct supersensuous perception of reality. The Western psychologist Carl Jung made a serious attempt to read and understand Patañjali’s Yoga Sūtras. Thus it is of interest to compare to Jung’s understanding of mystical experience with that of Patañjali. We will begin with Patañjali.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.018
Scholarly communication0.0030.004
Open science0.0000.002
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 head0.060
GPT teacher head0.406
Teacher spread0.346 · 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 designTheoretical or conceptual
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

Citations0
Published2013
Admission routes1
Has abstractyes

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