Bibliographic record
Abstract
This methodological paper describes the theory and practice of a biblio/poetry therapy workshop prepared and offered at the first European Biblio/Poetry Therapy Conference in Budapest, on 4-5 October 2024. The authors combined their work in autoethnography, Dialogical Self Theory and Jungian psychology, using poetry to explore the internal monologue and duologue, and autoethnographic prose to explore the multiple voices representing the many different parts of the self. The purpose of this workshop was that those writing might become more intimately acquainted with the concept of inner voice: how to define it, how to tune into it, listen to it, and capture it – or try to keep up with it – on the page. The presentation combined: a narrative introduction to the way inner voice influenced the authors’ own development journeys; theoretical frameworks, from which they each facilitate others; and poetry and prose prompts, to initiate participants into attempting their own 'inner voice' writing. The final process included optional sharing of work by reading it aloud, followed by a period of dialogical reflection on what had been shared. This workshop offered specific methods and exercises – grounded in psychological theory and the established principles of biblio/poetry therapy facilitation – to those wishing to guide others in learning about the self through writing.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.064 | 0.024 |
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".