Effects of tourism growth in a UNESCO World Heritage Site: resource-based livelihood diversification in the Galapagos Islands, Ecuador
Bibliographic record
Abstract
In the Galapagos, as elsewhere, tourism is promoted as a means of reconciling biodiversity conservation interests with the economic aspirations of local populations. However, the rapid expansion of tourism has triggered concerns about both social and biophysical impacts that may threaten sustainable development of the islands. These concerns, coupled with mounting constraints imposed by conservation regulations, have particular significance for two locally important resource-based livelihoods: fishing and agriculture. This paper examines recent patterns of livelihood diversification within these two sectors, and explores reasons behind livelihood decisions that people make, either to maintain existing resource-based activities or to transition into emergent livelihood opportunities. We examine drivers and inhibitors of diversification, focusing particularly on opportunities associated with tourism growth. Through a mixed-methods approach, we explore the perceptions, motivations, and actions of those still engaged in farming and fishing on the Galapagos’ three most populated islands. Results show that many are drawn to tourism, but there are notable differences in the appeal of, and the obstacles to, diversification. Considering the importance of both conservation and tourism in this iconic destination, these findings have significant implications for the role of sustainable tourism on the islands, and for the optimization of the conservation-tourism alliance elsewhere.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".