Astrotourism as Social Innovation for Peripheral Territories: Pathways for Sustainable Development Under Dark Skies
Bibliographic record
Abstract
Astrotourism is gaining international recognition as a practice that integrates science, culture and sustainability, addressing global challenges such as light pollution and fostering inclusive local development. Although its environmental and economic impacts are widely acknowledged, its potential as a driver of social innovation remains underexplored. This study addresses this gap by examining how astrotourism activates social innovation across multiple governance scales. The objective is to identify the mechanisms, enabling conditions, and territorial arrangements through which astrotourism operates as social innovation in peripheral contexts. The research adopts a qualitative and exploratory approach, based on documentary and bibliographic analysis of four international cases: Alfa Aldea in Chile, Dark Sky Alqueva in Portugal, the Jasper Dark Sky Festival in Canada, and the National Astrotourism Strategy in South Africa. A comparative framework was applied to identify three recurrent dimensions of social innovation—social capital, redistribution of power, and collaborative responses to crises—drawing on both classical and contemporary literature. Findings show that, despite institutional and territorial differences, all four cases demonstrate the capacity of astrotourism to build trust networks, strengthen community protagonism, and generate adaptive responses to socioeconomic vulnerabilities. The study proposes an interpretive matrix that outlines pathways of social innovation, offering policymakers tools to design multi-scalar strategies that connect community initiatives with national frameworks to achieve the Sustainable Development Goals. Beyond astrotourism, the framework also provides insights for other sustainable tourism modalities based on natural and cultural heritage.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".