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Record W2170759063 · doi:10.1177/1363461514557561

Is mindfulness Buddhist? (and why it matters)

2014· article· en· W2170759063 on OpenAlexfundno aff
Robert H. Sharf

Bibliographic record

VenueTranscultural Psychiatry · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicIndian and Buddhist Studies
Canadian institutionsnot available
FundersMcGill University
KeywordsBuddhismMeditationMindfulnessDoctrinePsychologyBuddhist philosophyCriticismAestheticsEpistemologySociologyPsychotherapistPhilosophyLawPolitical science

Abstract

fetched live from OpenAlex

Modern exponents of mindfulness meditation promote the therapeutic effects of "bare attention"--a sort of non-judgmental, non-discursive attending to the moment-to-moment flow of consciousness. This approach to Buddhist meditation can be traced to Burmese Buddhist reform movements of the first half of the 20th century, and is arguably at odds with more traditional Theravāda Buddhist doctrine and meditative practices. But the cultivation of present-centered awareness is not without precedent in Buddhist history; similar innovations arose in medieval Chinese Zen (Chan) and Tibetan Dzogchen. These movements have several things in common. In each case the reforms were, in part, attempts to render Buddhist practice and insight accessible to laypersons unfamiliar with Buddhist philosophy and/or unwilling to adopt a renunciatory lifestyle. In addition, these movements all promised astonishingly quick results. And finally, the innovations in practice were met with suspicion and criticism from traditional Buddhist quarters. Those interested in the therapeutic effects of mindfulness and bare attention are often not aware of the existence, much less the content, of the controversies surrounding these practices in Asian Buddhist history.

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)0.004
metaresearch head score (Gemma)0.007
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.021
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.222
Teacher spread0.202 · 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
GenreCommentary

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

Citations184
Published2014
Admission routes1
Has abstractyes

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