The Found Poem as a Pedagogical Strategy for Promoting Self-Authorship for Practice
Bibliographic record
Abstract
This chapter explores the question does the use of the found poem—a poem constructed by assembling a series of phrases from a series of readings—promote self-authorship in a professionally oriented graduate program. The chapter begins by arguing that self-authorship is a necessary condition to being an effective practitioner, followed by outlining self-authorship, its relationship to practice and higher education. This is then followed by laying out the practice context for the use of the found poem, a graduate course in the Capacity Development and Extension program at the University of Guelph. We then discuss the use of the found poem and how its use changed over time. In the following section two former participants in the class, who are now practitioners, share their reflections on the found poem followed by the instructor's reflections. We then discuss the implications for its use and attempt to answer the question does the found poem facilitate the development of self-authorship?
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".