Factors Influencing Property Owners’ Attitudes toward Different Orientations of Sustainability
Bibliographic record
Abstract
The southeastern United States is well-known for its natural beauty, warm year-round climate, and vacation and outdoor recreational opportunities. This study explores and compares factors influencing property owners’ attitudes toward different scales of sustainability in three coastal counties in North Carolina. In this region, tourism is the major economic driver, with second homes comprising nearly 40% of the total single-family housing stock. The research questions of this study then are: 1) Which factors influence property owners’ attitudes toward sustainable tourism development? 2) Does residential status (full-time residents vs. second-home owners) best predict property owners’ attitudes toward different scales/orientations of sustainability? 3) Which variables most contribute to predicting property owners’ attitudes toward different scales/orientations of sustainability? A total of 1,278 respondents were surveyed concerning their perceptions of sustainable development, satisfaction with community life, and attitudes toward tourism and second-home development. Factor analyses were conducted to identify three different orientations of sustainability as identified by the researchers: operational-oriented sustainability, community-oriented sustainability, and normative-oriented sustainability. Multivariate regression analyses were used to identify and compare factors which have significant influences on attitudes toward orientations of sustainability among different types of property owners. The study results are intended to inform decision-making that will contribute to the long-term economic, environmental, and socio-cultural sustainability of these counties.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".