Our responsibilities for future generations from a social-emotional learning perspective: revisiting mindfulness
Bibliographic record
Abstract
This article provides the readers with an opportunity to revisit the original purpose of mindfulness and to learn about some concerns and challenges raised in current understandings and practices of mindfulness, in order to make our mindfulness-based practices more effective and relevant, deriving in part from a perspective of social-emotional learning. Over the past several decades, mindfulness has gained increased attention within the clinical and educational settings, especially as intervention practices. The prevalence of mindfulness-based practice use has tripled between 2012 and 2017 among adults; the prevalence among children aged 4 to 17 years increased 9 times from 2012 to 2017, according to a recent national survey in the U.S. Given such a wide and steady rise in attention, our scientific interest in mindfulness has increased dramatically over the past two decades. However, we still have much work to do to translate appropriate knowledge and skills into effective practice.
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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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.007 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.018 |
| Insufficient payload (model declined to judge) | 0.007 | 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".