Forest Kindergarten: A qualitative case study comparing the emergent and play-based \ncurriculum at Cedarsong Nature School to the Newfoundland and Labrador Kindergarten \nCurriculum
Bibliographic record
Abstract
Kindergarten is a German word, meaning children’s garden. Today, professionals and \nparents around the world are speaking up and supporting the research that suggests young \nchildren benefit from time spent outside in natural environments and green, wild spaces. \nSome names for these programs are: Forest Kindergarten, Nature Kindergarten, or Forest \nSchools. \nIn this qualitative study I provide a descriptive narrative single case study \ncomposed of topic-centered narratives revealing significant themes and rich descriptions \nof a Forest school. The research questioned whether the expectations of the \nNewfoundland and Labrador Kindergarten Curriculum could be achieved using a Forest \nKindergarten model. The data for this case study was collected through interviews, \nobservations, field notes, artifacts, photographs, video recordings, and audio-visuals to \nexamine the concept of Forest Kindergarten as implemented by Cedarsong Nature \nSchool on Vashon Island, WA. \nUpon investigation, the researcher concludes that Forest Kindergarten programs \ndo meet and offer children learning opportunities to reach beyond the specific curriculum \noutcomes specified for the kindergarten curriculum in Newfoundland and Labrador. The \nfindings suggest the advantages of a Forest Kindergarten program include advanced \ncommunication, social, and critical thinking and problem-solving skills, a stronger sense \nof self, place, and community, as well as the importance of creative play-based learning \nand sensory-based play. It is recommended that the Forest Kindergarten model be \nconsidered for Newfoundland and Labrador schooling in particular Aboriginal \ncommunities and schools.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".