Encountering a stranger during a forest walk
Bibliographic record
Abstract
The primary purpose of this study is to investigate the effects of encountering another person during a forest walk and it's impacts on restoration.The MIST (Montreal Imaging Stress Task) was employed to create cognitive and physiological stress in 82 students.Three different conditions either simulated an encounter with a stranger, an encounter with an acquaintance or a situation with no encounter.During the whole procedure the heart rate was assessed.The PANAS (Positive and Negative Affect Scale) evaluated participants' individual perception of the situation as well as several self-report measurements evaluated the experience of restoration and contact experience and the attitude towards the walk.Results of the PANAS revealed a higher rating of the positive contact scale in the stranger condition than in the no-encounter condition as well as in the acquaintance condition.Results of the analysed heart rate change revealed that participants of the acquaintance condition underwent a declined level of restoration compared to participants of the stranger condition.Summing up, these findings show that participants of the acquaintance condition evaluated their situation less positive and restored worse than participants of the stranger condition.How positive did you think of encountering Dr. Wit during the walk?How annoying did you find it meeting Dr. Wit during the walk?How stressful did you find it meeting Dr. Wit during the walk?The value of the internal consistency of the specific questions regarding condition 3 had a good Cronbach's alpha of .89(α= .89).How comfortable do you find this environment to walk in?How much do you like to walk in general?How often have you walked for about an hour in this kind of environment in the past three months?How well did the video represent a real walk in a natural environment?How well did the video match your image of a natural environment?How natural did you find the surroundings of the walk? 5.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".