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Record W7133463541

Beyond the fence: Exploring forest preschool/school approaches in Australia

2017· other· en· W7133463541 on OpenAlexaboutno aff
Sue Elliott, Barbara Chancellor

Bibliographic record

VenueRUNE (Research UNE) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCultural diversityTraditional knowledgeCultural influence
DOInot available

Abstract

fetched live from OpenAlex

The origins of forest preschool/school approaches are attributed to Scandinavian countries, where children can frequently be found playing outdoors in all weathers as an integral aspect of their education programs (Knight, 2013a; Willia1ns-Siegfredsen, 2012). Such approaches are linked intrinsically to Scandinavian culture and landscape, specifically in Denmark, where WilJiams-Siegfredsen (2012, p. 7) describes frilufts/iv, or the 'free air life', as a long-standing cultural tenet. While forest preschools for young children up to the school-entry age of 6 years have been common in Scandinavia for decades, only in the 1990s was the forest preschool approach introduced into the United Kingdom. Since the 1990s, there has been an exponential growth in this approach across both preschools and schools, and internationally in many countries, including Australia, Ca11ada, Japan, New Zealand and the United States (Knight, 2013b). In Canada and the United Kingdom, this growth has recently led to over-arching professional associations, the Canadian Forest School Association and the United Kingdom Forest School Association, which offer guiding principles, practical information, publications, research and collaborative potential.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0050.002
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0040.031

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.

Opus teacher head0.492
GPT teacher head0.424
Teacher spread0.068 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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