Discussing the socio-economic impacts of tourism development projects based on golf courses: the perspective of local stakeholders
Bibliographic record
Abstract
In this paper, we present some results extracted from a social impact study carried out on a golf-based tourism development project (GBP). A phronetic approach is adopted, underpinned by case study methodology. The main objective of the article is to shed some light on the debate over the profitability of GBPs. To this end, firstly, we define GBP and briefly set out the sociological and economic reasons for their growth. Secondly, we describe the specific case studied and our analytical approach, based on (1) analysis of the financial balance and prospects of the business in question, and (2) qualitative analysis of the views of local stakeholders. Discussion of our data enables us to assess to what extent a GBP can be deemed beneficial or not, highlighting the need for holistic, multidimensional and locally-based analysis to suitably evaluate GBPs as an appropriate model for sustainable development.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".