Exploring resource-providing vacation activities and recovery experiences: a study in the context of Goa
Bibliographic record
Abstract
In our fast-paced world, work-related stress takes a toll on health and well-being. To address this, individuals seek respite through vacations. Employing a mixed-methods approach, data were collected from 422 participants through on-site and online surveys, analyzing engagement in activities and their influence on psychological detachment, relaxation, control, and mastery. Factor analysis revealed seven distinct vacation dimensions – outdoor activities, cultural activities, entertainment, social activity, nature recreation, shopping and light recreation. Findings revealed that engagement in entertainment, light recreation, social, and cultural activities positively affect psychological detachment. Outdoor activities, nature recreation, and entertainment enhance relaxation. Light recreation and shopping boost visitors’ sense of control, while social activities promote mastery. This research highlights the importance of tailored vacation activities for enhancing recovery and overall well-being. It offers insights for researchers and practitioners alike, emphasizing the need to meet tourists’ recovery needs for enriched vacation experiences and enhanced well-being.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".