MétaCan
Menu
Back to cohort
Record W1963936150 · doi:10.3390/rel5030560

Between Buddhism and Science, Between Mind and Body

2014· article· en· W1963936150 on OpenAlexfundno aff
Geoffrey Samuel

Bibliographic record

VenueReligions · 2014
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
FundersUniversity of Toronto ScarboroughUniversity of Toronto
KeywordsBuddhismContext (archaeology)MindfulnessMeditationEpistemologyRelation (database)AestheticsRewritingPhilosophyHistorySociologyArchaeologyTheology

Abstract

fetched live from OpenAlex

Buddhism has been seen, at least since the Theravāda reform movements of the late nineteenth and early twentieth centuries, as particularly compatible with Western science. The recent explosion of Mindfulness therapies have strengthened this perception. However, the 'Buddhism' which is being brought into relation with science in the context of the Mindfulness movement has already undergone extensive rewriting under modernist influences, and many of the more critical aspects of Buddhist thought and practice are dismissed or ignored. The Mind and Life Institute encounters, under the patronage of His Holiness the Dalai Lama, present a different kind of dialogue, in which a Tibetan Buddhism which is only beginning to undergo modernist rewriting confronts Western scientists and scholars on more equal terms. However, is the highly sophisticated but radically other world of Tantric thought really compatible with contemporary science? In this article I look at problem areas within the dialogue, and suggest that genuine progress is most likely to come if we recognise the differences between Buddhist thought and contemporary science, and take them as an opportunity to rethink scientific assumptions.

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)0.003
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.010
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.074
Scholarly communication0.0100.007
Open science0.0010.006
Research integrity0.0030.009
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 head0.029
GPT teacher head0.340
Teacher spread0.311 · 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

Citations28
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueReligionsSame topicMindfulness and Compassion InterventionsFrench-language works237,207