“Confident, Supportive, and Capable”: A Retrospective Analysis of an Outdoor Orientation Program
Bibliographic record
Abstract
Background: Initial effects of participation in outdoor orientation programs (OOPs) have been well-documented. However, there are few studies that examine longitudinal outcomes. Purpose: This study explored the long-term effects of engaging in an OOP. Methodology/Approach: This study employed the Most Significant Change technique and implemented a retrospective qualitative approach to understand the meaningful lessons participants learned as well as long-term outcomes they perceived as being important today. Alumni from an OOP (both participants and leaders) were questioned using semistructured interviews. Thematic analyses, using a constant comparison data analysis method, included open coding, focused coding, and axial coding. Findings/Conclusions: Major themes that emerged included understanding self, building community, and belonging to nature. Participants reported long-term impacts related to coping, stress relief, resiliency and thriving, relationship skills, sense of community, and environmental appreciation. The overarching theme of health and well-being was described as a long-term impact by participants. Implications: Results provide confirmation of positive long-term effects of OOPs and outdoor expeditions. Researchers and practitioners can use these results to better market programs to potential participants and parents, demonstrate the efficacy of OOPs to stakeholder groups, and inform staff training and program curricula.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".