Living and Learning with Morningside Blackberry Plant: Re-thinking our Relationship with the World
Bibliographic record
Abstract
This living inquiry took place in the Morningside early learning program at the SFU Childcare Society as part of a practicum course. As we entered the program in early September, our attention was grasped by the children's and educators' engagement and encounters with a particular blackberry plant residing in the corner of the Morningside yard. The Morningside blackberry plant is an integral part of the daily life of the program as the children regularly visit this unique plant, spending time under its tall branches, observing the bubbly blackberries, and reaching over to pick them in their mouths. However, the desire of the children to pick as many berries as they could reach raised discussion and discomfort about the berry plant being viewed solely as an object – a resource for human consumption. And so, as practicum students entering a space with these concerns, we began to consider how we might shift the focus on living and learning with and knowing the berry plant differently and transform our perspective on the world through a curriculum inquiry. This Pedagogical Narration highlights particular events, becomings, and transformations that emerged from children's curiosity and encounters with the blackberry plant and its spikes that provoked the children to re-think their relationship with the world and more-than-human others.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.032 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".