Slowing, Desiring, Haunting, Hospicing, and Longing for Change: Thinking With Snails in Canadian Early Childhood Education and Care
Bibliographic record
Abstract
This paper is a collective attempt to respond creatively to a research project we were part of entitled Sketching Narratives of Movement: Towards Comprehensive and Competent Early Childhood Educational Systems Across Canada. We share our slow process of thinking, collaborating, wondering, and pausing along with the figure of the snail as we improvise a nonlinear path towards an unknown future. We think-with various theories of change as a response to narratives shared by participants in the project’s knowledge mobilization events: two public webinars and the production of a series of short video interviews. The pandemic simultaneously (re)inscribed ECEC with familiar discourses and narratives, yet, it also issued forth the potential for new imaginaries. ECEC was suddenly positioned as a critical community life-sustaining space for entire systems stressed by a pandemic. Amidst the attention, however, “slimy” traces of chronic neglect, underfunding, and undervaluing of ECEC were gleaming. Given the unpredictable momentum, we argue that it is essential that we open up ECEC to different narratives of movement. To this end, we offer five theoretical capsules titled: Slowing, Desiring, Haunting, Hospicing, and Longing as provocations for storying care otherwise and for stirring ethical consideration with potentialities for slow activism in ECEC. Keywords: Early childhood education and care, Canada, theories of change, slow activism, haunting, hospicing, desire
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.047 | 0.055 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| 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".