Bibliographic record
Abstract
During the initial years of the L.E.A.D. program, one of its core values was to incorporate Outdoor and Experiential Education (O.E.E.) for students identified as ‘in-risk' of not graduating. Teacher candidates at the University of Windsor enrolled in the L.E.A.D. program were encouraged to embrace O.E.E. to assist students in building skills that promote overall personal and social development. A major component of the L.E.A.D. program was for teacher candidates to plan O.E.E. activities such as a 3-day overnight camping excursion and a retreat to the Ojibway Nature Centre and Ojibway Park. Embarking on these O.E.E. activities with selected secondary school students deemed to be ‘in-risk' accompanied by a group of caring adults provided the opportunity for rich outdoor experiences for all participants. This chapter highlights and explores the various O.E.E. activities experienced by L.E.A.D. teacher candidates and L.E.A.D. program students ‘in-risk', and shares research that describes the benefits of participation in O.E.E.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.519 | 0.349 |
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".