The Biophilia Effect: Expanding Green Horizons in a Global Workplace
Bibliographic record
Abstract
This symposium explores the growing evidence that nature contact -- ranging from biophilic office design to immersive outdoor experiences -- may exert profound effects on employee well-being, work engagement, and organizational outcomes. As rapid urbanization continues to limit daily exposure to natural elements, research increasingly points to nature as a powerful yet underexamined resource for sustainable management practice. In this session, five presentations illuminate multiple facets of the “Biophilia Effect.” First, we see how even simple interventions, such as workplace greenery, boost employee energy and dedication. Next, we learn how entrepreneurs and boundaryless workers may strategically leverage nature for real-time recovery. We then turn to an ethnographic study that reveals how specific environmental contexts (e.g., remote islands, mountainous terrain) mold employees’ work-life boundaries. A fourth paper uncovers moral complexities in (animal) caregiving professions, where necessary evils can cause psychological and ethical tension. Finally, we broaden our view by examining user acceptance of wooden housing, underscoring how green innovations can shape both corporate strategies and societal well-being. Collectively, these papers provide timely, high-impact insights for scholars across OB, ONE, and SIM, illustrating how nature-based approaches can enrich individuals’ work experiences, advance sustainable organizational practices, and foster responsible management in a globalized world. Biophilic Design at Work: Investigating How Greenery Supports Employee Engagement Author: Meredith Jordan Pool; Clemson University Author: Robert R Sinclair; Clemson University Detachment vs. Absorption in Nature: A Person-Centered Approach to Employee Recovery Breaks Author: J. Jeffrey Gish; University of Central Florida Author: Ute Stephan; King's College London Author: Jon C. Carr; North Carolina State University Author: Réka Anna Lassu; Pepperdine University Author: Sarah Burrows; Queen's University Author: Jeffrey M. Pollack; North Carolina State University The Topography of Work-Life Boundaries: How Environmental Context Shapes Work-Life Navigation Author: Elena Maria Wong; University of Pennsylvania The Mixed Consequences of Necessary Evils in the Veterinary Profession Author: Carisa Lam; Author: Vanessa Liu; User Acceptance of Wooden Housing: Green Future in the Construction Industry? Author: Malgorzata Iwanczuk-Prost; Wageningen University and Research Author: Emiel F.M. Wubben;
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 | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".