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Record W2590939732 · doi:10.5430/ijhe.v6n2p1

Calming the Monkey Mind

2017· article· en· W2590939732 on OpenAlexaffvenue
Kendra Eliuk, David Chorney

Bibliographic record

VenueInternational Journal of Higher Education · 2017
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMindfulnessAnxietyPsychologyStress (linguistics)Control (management)Developmental psychologyCognitive psychologySocial psychologyPsychotherapistComputer science

Abstract

fetched live from OpenAlex

Many of today’s students are experiencing higher levels of stress and anxiety in school. The need for competitive grades, the desire to be seen as perfect in a digital society, and parental pressures are only some of the reasons that students are experiencing more stress. This increased stress has lead to an overworked mind for many youth, dubbed a ‘monkey mind’ in which they cannot calm or control their thoughts. This article examines possible causes of a ‘monkey mind’ and explores the beginning of how students may learn to calm and control their ‘monkey mind’ through mindfulness training. Several examples of mindfulness training in different classroom scenarios are introduced, and the relationships between our connections to everything around us are explored. The article serves to provide a starting point for educators who may feel at a loss for how to help their students manage their stress and anxiety levels.

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)0.001
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.004
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.048
GPT teacher head0.433
Teacher spread0.385 · 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
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

Citations6
Published2017
Admission routes2
Has abstractyes

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