Using engaged philosophical inquiry to deepen young children’s understanding of environmental sustainability: Being, becoming and belonging
Bibliographic record
Abstract
This research paper shares findings related to our use of Engaged Philosophical Inquiry (EPI) with a group of young children (aged 3-4) as a pedagogical method taken up to extend young children’s thinking about human use of forest parkland and to determine the children’s ontological positions related to environmental sustainability. The study was conducted in a forested area adjoining a ‘living building’ childcare centre. Here researchers, along with a core group of 9-13 children, their teachers, and a Philosopher-in-Residence (Warren Bowen) visited the forest environment on a fortnightly basis over a four-month period from January to May 2016 to explore the forested area, play games and discuss issues related to forest use and human habitation. Video records of the EPI sessions were transcribed and analysed to determine the children’s propositions and related ontological stance(s) across sessions. Findings from this study include: (1) evidence that young children’s views on stewardship are situated within socio-material manifestations of belonging, ownership, and entitlement within the forest; and (2) that absurdities, along with other more traditional EPI and P4C strategies, can be used successfully to playfully challenge young children’s thinking about the rigour of their propositions and to provoke deeper thoughts related to belonging and care.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".