The intermingled meanings of<scp>PhoneMe</scp>: Exploring transmodal, place‐based poetry in an online social network
Bibliographic record
Abstract
Abstract This research paper explores how preservice teachers engaged with the transmodal place‐based poetry on PhoneMe, an educational social media platform for sharing poetry and vocal performances about place. This work is situated in literature on digital place‐based education and theoretical scholarship exploring transmodality and the shifting entanglement of meanings and modes. In this paper, we share findings from a research survey conducted with teacher candidates in a core teacher education literacy course that had transitioned online due to the COVID‐19 pandemic. We discuss how participants engaged with the transmodal poetry in the survey and how their perceived poetic meaning and poetic connections changed with each additional modality. We share the pedagogical implications of our findings as well as ideas gleaned from the data for integrating the PhoneMe platform and pedagogy in secondary school classrooms. In the discussion, we explore how engagement with transmodal place‐based digital poetry can be a unique way to draw together place‐based education, digital literacies, social media literacies, and poetry pedagogy in a way that is visceral, relational, and highly relevant to contemporary lives and classrooms both on and offline.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".