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Record W3121268020 · doi:10.31234/osf.io/6zs5g

Mindfulness and Legal Practice: A Preliminary Study of the Effects of Mindfulness Meditation and Stress Reduction in Lawyers

2017· preprint· en· W3121268020 on OpenAlexaff
John Paul Minda, Jeena Cho, Emily Nielsen, Mengxiao Zhang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicWorkaholism, burnout, and well-being
Canadian institutionsWestern University
Fundersnot available
KeywordsMindfulnessMeditationAnxietyPsychologyMoodMindfulness meditationPsychotherapistStress reductionClinical psychologyPsychological resiliencePsychiatry

Abstract

fetched live from OpenAlex

Research has shown that lawyers often experience symptoms of depression, anxiety, and stress in their lives. Mindfulness meditation may be an effective way to reduce the many negative effects associated with work stress. We asked a group of 46 lawyers to participate in an eight week mindfulness meditation program that was designed for lawyers. The mindfulness program was based on The Anxious Lawyer by Cho and Gifford (2016) and guided audio meditations were made available online. Participants were assessed before beginning the program and again when the program was completed. The results indicated that the mindfulness meditation program significantly reduced self-described depression, anxiety, stress, and negative mood. The meditation program also increased positive mood and psychological resilience. As well, participants in the program viewed themselves as being more effective at their work. Despite the strong effects observed in this study, we argue that much more research is needed to understand these benefits.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.320
Teacher spread0.308 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2017
Admission routes1
Has abstractyes

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