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A Mindfulness Journey: Finding Spiritual Renewal Through Contemplative Prayer

2025· book-chapter· en· W7093099563 on OpenAlexaff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsBishop's University
Fundersnot available
KeywordsMindfulnessContemplationPrayerSpiritualityWell-beingSkepticismIntervention (counseling)

Abstract

fetched live from OpenAlex

Abstract This chapter explores the impact of combining mindfulness practices and a companionship experience with a tree. The author’s weekly mindfulness exercises and establishing a mindful relationship with nature guided her to develop an understanding of the principles and benefits of using mindfulness for personal growth. The author also navigated a personal crisis by forming a mindful relationship with a tree. Integrating contemplative prayer inspired by the life of Saint Francis of Assisi and the writings of Franciscan priest Richard Rohr in her mindful experiences, the author develops a new understanding of the self. This chapter traces the journey from being skeptical about mindfulness, through the struggle to successfully practice mindfulness, to building a personal approach to mindfulness rooted in contemplative prayer, a journey that fostered strength, solace, and spiritual renewal.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.089
GPT teacher head0.368
Teacher spread0.279 · 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
Published2025
Admission routes1
Has abstractyes

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