Wild Pedagogies and Young Children through the Mosaic Approach
Bibliographic record
Abstract
Abstract This paper reports on a doctoral study that explored young children’s (ages 5 to 7 years) relationships with sticks during their school-based outdoor learning experiences. Sticks (parts of trees) became uniquely contextual agents due to the profound agentic effect the stick-based experiences, which were enacted through Wild Pedagogies, had on the children’s understandings of Place. Sticks were used in physical and symbolic ways throughout the children’s self-guided learning experiences. The children used long sticks to build large structures, houses, and other creations, and selected smaller sticks to represent microphones, brooms, or currency. The use of the Mosaic approach in this study aligns with Wild Pedagogies’ openness to new and different ways of being in and understanding the world, particularly as this approach privileges children, natural objects, and Place as agentic co-teachers and co-learners. The children demonstrated their agency as they made cognitive, physical, corporeal, agentic, affective, and aesthetic connections with Place, which they expressed through their Wild Pedagogical experiences. The study underscores the value of tactile, immersive, and bioregional experiences in helping children connect with nature, build knowledge, develop and share collective agency, and cultivate an ethic of care for the environment in Wild Pedagogical ways.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".