Collaborative Poetry Making: Words, Place, and Decolonisation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores how poetry can contribute to the work of decolonisation for faculty development professionals and academic faculty more broadly. It explains how poetry has been significant for the authors in constructing and deconstructing our understandings of place. Through a discussion of literary theorists as well as Indigenous and non-Indigenous poets, it then considers how poetry might provide avenues for the personal and emotional work necessary for decolonisation. We share the process of a collaborative poetry workshop that we engaged in with participants at the 2019 Intercultural Intersections Conference at Thompson Rivers University, providing an overview of the practice and samples of the resulting poems. Through an analysis of these poems and the process itself, we consider the implications of this activity as a decolonising exercise.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it