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Record W3090358761 · doi:10.1108/jced-06-2020-0005

Virtue as Emergence From Contemplative Practices

2020· article· en· W3090358761 on OpenAlexaff
Jing Lin, Tom Culham, Charles Scott

Bibliographic record

VenueJournal of Character Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsContemplationVirtueEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

In this article, we argue that virtues can emerge from contemplation which can lead us to attunement with the Dao thereby realizing our inner goodness and intrinsic traits. This requires us to persist in doing inner and outer work. Inner work involves meditation and reflective practices to awaken ourselves and others. Outer work involves engaging others and ourselves with loving-kindness, compassion, joy, and equanimity. The article discusses the transformative perspectives and practices in Daoist, Confucian, and Buddhist contemplative traditions that lead to the development of virtue and alignment with the Dao; further, it examines contemporary contemplative practices and new scientific discoveries, providing evidence that virtues of a leader can emerge from within. In other words, virtues can be cultivated, and there are rich traditions and methods in both Western and Eastern philosophies and religions that facilitate the emergence of virtues through contemplative and other religious practices. Character building and virtue training are linked to inner contemplative work, which we argue need to be integrated with cultivating vital life energy and doing good for the world. Character education and transformation are much more effective when supported by contemplative practices and inner work because changes come from deep within the heart. The integration of these two elevates our awareness of our interconnectivity with all and enhances our ability to serve the world lovingly and humbly, which are hallmarks of virtuous behaviors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.418
Teacher spread0.338 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations3
Published2020
Admission routes1
Has abstractyes

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