Inspiring Educators and a Pedagogy of Kindness: A Reflective Essay
Bibliographic record
Abstract
The purpose of this reflective essay was to explore the literature on educators that employ kindness as an approach to pedagogy in higher education. Through a series of reflections, we then considered how educators using a teaching philosophy guided by a pedagogy of kindness influenced learners’ lives, enhanced their social consciousness, and facilitated meaningful learning. To begin, we summarized research reports from peer-reviewed journals and articles from grey literature. Questions that guided the literature search were, how does the use of a teaching philosophy based on a pedagogy of kindness affect the learning environment for students and does it modify their attitudes towards social injustice, does this teaching philosophy improve academic outcomes for learners, and is there a possible link between a pedagogy of kindness and teaching success? In sum, the literature revealed that a teaching philosophy based on a pedagogy of kindness is a common approach used by inspiring educators. Further, this teaching philosophy positively influences students, their learning environments, their educational achievements, and engages them to reflect on issues of social justice. A pedagogy of kindness also results in increased career fulfillment for teachers. Our reflections provide examples of these conclusions.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".