Bibliographic record
Abstract
Presently, there is much literature from physical health, mental and social wellbeing, environmental and sustainable development, and curriculum and pedagogy research evidencing need to increase outdoor learning experiences for students. While efforts to increase outdoor learning exist in curricular and instructional design discourses, there seem to be barriers limiting efficacy and proliferation of outdoor learning experiences in practice. Teacher education programs and in-service professional development in Faculties of Education most commonly focus on curriculum and pedagogy. Outdoor Education is neither discipline nor didactic, and it is a struggle to situate outdoor learning experiences within curricular or pedagogical camps (Beams, Higgins and Nicol, 2012. As Outdoor Education belongs to neither, it is suggested that it has its own category of place , with unique characteristics (ontology) requiring distinct approaches (epistemology). Curriculum is situated as principally concerned with what and pedagogy with who , thus place is permitted to be contemplated as where . Where may be physical (indoor/outdoor), or mental (memory), or cybernetic (chat room). Place , as unique category for Educational discourse, in turn may allow redress of historic marginalization faced by Outdoor Education, shifting emphasis from curricular and pedagogical rhetoric towards enabling more outdoor learning during instructional times.
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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 | 0.039 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.026 | 0.142 |
| Scholarly communication | 0.043 | 0.071 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".