Maddening pre-service early childhood education and care through poetics: Dismantling epistemic injustice through mad autobiographical poetics
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
In this article, the author forwards the importance of mad autobiographical poetic writing to challenge and disrupt epistemic injustice within pre-service early childhood education and care. They explore their own mad autobiographical poetic writing as a queer, non-binary, mad early childhood educator and pre-service early childhood education and care faculty member, and argue that mad poetic writing can methodologically be used as a form of resistance to epistemic injustices and epistemological erasure in early childhood education and care. This article argues for the importance of autobiographical writing in early childhood education and care, and the necessity of centralizing early childhood educators' subjectivities and histories when addressing - and transforming - issues of equity, inclusion and belonging in early childhood education and care. The personal and intimate mad autobiographical poetic writing of this article - written by the author - focuses on how personal experience with madness as it pertains to working within pre-service early childhood education and care can challenge norms that govern and regulate madness. Ultimately, the author argues that transformation in early childhood education and care can take place by reflecting on experiences of mental and emotional distress, and considering poetic writings as starting places for imagining new futurities and a plurality of educator voices and perspectives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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