Framing Maya culture: Tourism, representation and the case of Quetzaltenango
Bibliographic record
Abstract
This article examines the representation of Maya culture in travel and tourism literature. It compares and contrasts framings in historical, promotional and online tourist media. Two main tropes are identified that have been central to this literature since the mid-nineteenth century, culminating in a current practice described here as Maya cultural tourism. In Guatemala, promotional texts replicate earlier tropes to portray Maya culture as a primary source of attraction. What these dominant commercial framings consistently ignore, however, are Maya contributions to global tourism narratives and exchanges. To address this gap, the second part of the article focuses on the ways in which local actors use online media to present themselves to tourists in the case of Quetzaltenango. This serves to illuminate key differences in how tourism marketers and local actors package Maya culture for global consumption. It is concluded that overcoming a preoccupation with the same tired tropes involves paying closer attention to cultural narratives emerging in cyberspace that acknowledge Maya agency in their relations with tourists and portray these exchanges in a more nuanced and robust manner.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.019 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| 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".