Greening the guest bedroom: Exploring hosts’ perspectives on environmental certification for Airbnb
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The rapid rise of home-sharing and peer-to-peer accommodation has exposed new opportunities and issues in the hospitality industry. Given the heightened attention to and awareness of environmental issues in tourism and hospitality, this study explored the likelihood and motivations of Airbnb hosts towards participating in an environmental certification program. Currently, there are no such programs associated with Airbnb or this sector of the sharing economy. As part of this exploratory study, semi-structured interviews with Airbnb hosts in the Greater Toronto Area were conducted to uncover the opinions and motivations of Airbnb hosts towards participating in a potential program, and what program design elements would enhance their likelihood of participation. Results indicated a willingness to participate in an environmental certification program, driven by economic factors and personal values. Host opinions regarding preferred design elements provide insight into factors important to the development and success of such a potential program. Environmental certification is a common tool in tourism to signal environmental commitment by operators, but such a program does not yet exist for home-sharing.
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.
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 | 0.000 |
| Science and technology studies | 0.001 | 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 it