Bibliographic record
Abstract
This paper explores a common tension for parents and teachers working with young children – the tantrum. Building on practitioner-inquiry methodologies, I engaged in a living inquiry into my practices as a parent, with the initial goal of reducing or preferably eliminating my son’s angry outbursts. Frustrated with approaches informed by theories often applied within early learning contexts to address tantrums, including behavioural, attachment and self-regulation, I turned to new materiality theories, which provide a novel approach in understanding the socio-material constitution of subjectivities, emotions, and relationships. Within this assemblage, tantrums were reconfigured as a doing of emotions, occurring in the spaces in/between bodies, rather than an individual act of defiance. Through this inquiry, I shifted from a position of trying to intervene from the outside to eliminate, control or manage my son’s tantrums to a place of ‘intra-acting from within’ and journeying with. My parental inquiry became a site to continuously work and rework everyday life and participate in the creative practice of world making. Although the tantrums, which we came to know as Mad I’m mad, continued, the connection among and between my son and I shifted, often in positive and enduring ways. I came to understand parental inquiry as a practice of ‘wayfaring,’ where the focus is on the journey rather than the destination. These stories may ‘trace a path’ for other parents and educators as they participate within their own affective and embodied entanglements, creating new possibilities for teaching and learning relationships.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".