ANALYSIS OF THE PROMOTION OF THE HISTORIC CENTER OF MANAUS IN THE CITY'S PRINTED TOURIST GUIDES
Bibliographic record
Abstract
This article investigates the tourist promotion of the Historic Center of Manaus through the city's printed tourist guides. This analysis was prompted by a lack of promotional materials on the oldest central area of the city, whether in printed and digital media. Yet this is the locality with the highest concentration of cultural tourist attractions in Manaus, and it recognized through patrimonial protection at federal, state and municipal levels. The study analyzes the city's tourist guides, and their relationship with the tourism promotion of its historic center. Nine tourist guides were used, from different years, to determine whether they met the needs presented. The consultation of the guides characterizes the research as documentary, since the material was not submitted to analytical treatment. It is also defined as bibliographic, due to the construction of the theoretical contribution. The results demonstrated that the tourist promotion of the Historic Center of Manaus is insufficient in the guides consulted. In order to promote the area in question, the development of a tourist guide to the city’s oldest quarter is proposed, to be produced in both printed and digital formats, due to its historical importance and significant attractiveness in forming the image of Manaus as a tourist destination, qualified experience of visitors as well as the influence of the experience on the choice of tourist.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".