Bibliographic record
Abstract
In this essay I offer a series of autobiographical ruminations and poems for inviting readers to reflect on poetic possibilities for conceiving and fostering the well‐being of teachers. As an educator, I am confronted daily with challenges. In order to sustain my spirit and energy, I turn to poetry, both reading and writing poetry, and I find in poetry a location of wisdom, sustenance and hope. One of my great concerns about teaching is that the demands are so relentless that even the most dedicated teachers often experience burnout, dissatisfaction, ennui, hopelessness and despair. Therefore, I claim that teachers, both beginning and experienced, should learn to know themselves as poets in order to foster living creatively in the pedagogic contexts of classrooms and the larger pedagogic contexts outside classrooms. I invite both new and experienced teachers to consider the significance of a phrase like ‘living poetically’. I seek to contextualize the more practical and pragmatic considerations of teaching in an understanding of pedagogy as a poetic, emotional, personal, spiritual commitment and experience. My claim is simply that transformative learning can be effectively promoted by giving attention to poetry and poetic knowing and poetic living. I am learning to live poetically, and I am learning that the heart of pedagogy is revitalized and sustained by poetic knowing, being and becoming. Poetry engages us with language, nurtures the inner life, acknowledges the particular and local, encourages us to listen to our hearts, fosters flexibility and trust, and invites creativity and creative living.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.063 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".