Listening to Land as Teacher in Early Childhood Education
Bibliographic record
Abstract
This research responds to the Truth and Reconciliation Commission’s Calls to Action (2015) to develop “culturally appropriate early childhood education for Aboriginal families” by bringing together Elders, Knowledge Keepers, and educators to share their perspectives on land-based pedagogies for young children. This qualitative research is based on a ‘Circle Teaching’ shared by Ojibwe Traditional Teacher and Gokoomis (Grandmother) Jacque(line) Lavallee from Shawanaga First Nation in relationship to an Indigenous Knowledge Bundle that she calls a ‘Memory Teaching Bundle’. Since Spring 2019, this ‘Memory Teaching Bundle’ has been cared for and practiced cyclically through Seasonal Ceremonies led by Gokoomis (Grandmother) and her Oshkaabewis (Ceremonial Helper and Messenger) along Gaabikanang Ziibi (Humber River) in Tkaronto (Toronto) in collaboration with a group of Indigenous and non-Indigenous educators and community organizations committed to land-based early childhood education.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".