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Record W2304145305 · doi:10.11575/prism/5290

Learning to Breathe, Breathing to Learn: The Role of Mindfulness in Curriculum and Learning

2014· article· en· W2304145305 on OpenAlexaboutno aff
Kimberley Holmes

Bibliographic record

VenueOpen MIND · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsnot available
Fundersnot available
KeywordsMindfulnessCurriculumPsychologyPedagogyHolistic educationCognitionCognitive sciencePsychotherapist

Abstract

fetched live from OpenAlex

Teachers are not technicians but self-reflective individuals who work in a holistic manner to connect curriculum to cognitive, emotional and social contexts. Living up to this holistic vision requires teachers to “take seriously the idea that a child’s personal signature, his or her distinctive way of learning and creating, is something to be preserved and developed” (Eisner, 2002, p. 581). Inspiring Education (Alberta Learning, 2010) states that the goal of education is to create engaged, ethical and entrepreneurial citizens who have been “enabled to do well in life” (Eisner, 2002, p. 581). Actualizing this vision requires mindfulness with regards to curriculum and learning.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.008
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.290
Teacher spread0.269 · 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 designTheoretical or conceptual
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

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicNeuroscience, Education and Cognitive FunctionFrench-language works237,207