Bibliographic record
Abstract
Novel education research focuses on studying how teaching methods affect academic performance. A few minutes of mindful breathing during the beginning of each school day will help teach the students to better cope with daily stressors and reduce their overall anxiety. Mindful breathing is an experience of relaxing the body, quieting the mind, and awakening the spirit. It encourages a deepening of consciousness or awareness and facilitates deeper understanding of self and others. Studies have shown that teaching students about feelings and social interactions can increase their academic success and enhance the school experience in general. Mindful breathing can help students manage time, practice mindful eating, control addictions and cravings, reduce stress and enhance sleep, achieve academic success, achieve athletic success and body satisfaction, enhance the immune system, and develop a deeper sense of compassion for others and self. A 2008 U.S analysis of roughly 300 studies involving more than 300,000 students in elementary and middle school found that students who received social and emotional course (including mindful breathing exercises) scored 11 to 17 percentage points higher on achievement tests than peers who did not take part in any courses. Also, behavior issues decreased. This session is designed to inform teachers/instructors about the use of mindful-based practices in the classroom.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".