Bibliographic record
Abstract
In this paper, I explore practices for opening the heart and offering compassion towards others and also myself in the context of teaching. In doing so, I reflect upon experiences that involve the uneven distribution of “air time” in the classroom; I concentrate on such experiences because, as long-standing sources of irritation for me, I believe they can evoke insights about being present. How, for example, might I invite deeper awareness of my own being in such situations, notice how I am feeling in relation to the students, individually and collectively? How might I become better acquainted with my own resistances? Send love and compassion towards the students and also myself? Through contemplative practice, I observe my mind and habits of being. My aspiration is to teach from a softer, gentler place. I situate this work in relation to the literature in contemplative education, specifically that which offers insights into teachers’ inner work.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".