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Record W2411741118 · doi:10.26443/ijwpc.v3i2.118

Touching the compassionate heart: the ground of healing

2016· article· en· W2411741118 on OpenAlexvenueno aff
Kaveh Monshat

Bibliographic record

VenueInternational Journal of Whole Person Care · 2016
Typearticle
Languageen
FieldPsychology
TopicMemory, Trauma, and Testimony
Canadian institutionsnot available
Fundersnot available
KeywordsMindfulnessMeditationBuddhismNegotiationPsychotherapistWork (physics)Therapeutic touchPsychologyMedicineMedical educationAlternative medicineNursingSociologyPhilosophySocial scienceTheologyEngineering

Abstract

fetched live from OpenAlex

I am a psychiatrist, psychotherapist, secular mindfulness teacher and former university lecturer. Having conducted research in fields varying from laboratory molecular medicine to clinical applications of mindfulness, I took a two year sabbatical to focus on an inner search and healing. It was spent mostly spent in Plum Village: a Buddhist monastery in France in the tradition of Thich Nhat Hanh. I have recently returned to clinical work.I found that it was not until I took a compassionate view of myself that I truly began to heal; and that following my heart was the only way I could negotiate the uncertainties of the path.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.049
Scholarly communication0.0150.013
Open science0.0010.009
Research integrity0.0060.015
Insufficient payload (model declined to judge)0.0060.001

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 head0.049
GPT teacher head0.348
Teacher spread0.300 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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