Governance as Catalyst to Sustainable Tourism Development: Evidence from North Cyprus
Bibliographic record
Abstract
This study argues that sustainable tourism planning cannot be implemented unless institutions restructure their behaviors (i.e., the formal policy process) in close cooperation with the industry’s stakeholders (i.e., informal elements). What is missing in the case of North Cyprus is the concept of governance as distinct from government, which began to manifest when government became an organization apart from citizens rather than a process (Plumptre and Graham, 1999). Therefore, this study investigates the institutions that compromise the policy-making process of governance and its inferential outcomes for the purpose of achieving sustainability. Using a qualitative research strategy, a semi-structured interview questionnaire was administered. Interviewees were targeted within the relevant institutions based on purposive and snowball sampling. The underpinning conceptual framework that guides the methodology is based on the Environmental Sustainability Index (ESI, 2005) with emphasis on the component of ‘social institutional capacity’: governance. The study revealed the need for an institutional overhaul with an embedded process of governance as a new institutional culture. Furthermore, an institutional approach should accompany new practice methodologies for the way the tourism sector consumes places, produces products, and applies a conservation-based ethic to the natural and built environment.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".