Bibliographic record
Abstract
Amongst a group of poet-scholar friends, all of us students of the American poet Robert Bly, often speak of our “gratitude to old teachers,” the title from one of Bly’s (1999) poems. We cherish a meditative awareness of deeply rooted presences holding us up, buoying us as we stride across “Water that once could take no human weight” that now “holds up our feet / And goes on ahead of us ….” What is this mystery? Through the love and support of “old teachers,” we are held, led, and supported, into an unknown future that, without their guidance, we might never have reached. Many of Bly’s students (myself included) refer to how meeting him “changed” or even “saved” their lives. Similarly, I could say this of meeting and studying with Canadian curriculum scholar and poet Carl Leggo. Practicing gratitude to old teachers fosters vital pedagogic engagement and personal connection in a world often fraught with isolation and despair. Reflecting on how these poetic influences have inspired and guided my own personal and professional life, this essay ruminates on grateful legacies within literary and curriculum studies, and beyond. Keywords: gratitude, curriculum studies, mentorship, poetry, poetic inquiry
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.029 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".