Economics and Tourism as Agents of Global Connection: Garut Mid-19th Century to Mid-20th Century
Bibliographic record
Abstract
The beauty of Garut has been tempting many tourists to enjoy it since the early 20th century. Tourists who visit not only come from within but also from abroad. Studies on tourism in Garut have not received much attention. Scholars usually take Garut as a place of research; the topics discussed are related to social movements during the Dutch and Post-Independence periods. In Christian mission activities, there are multiple motives or impure motives. One of which is romantic motives, namely motives driven by the desire to go to distant and exotic lands and nations. So not infrequently, the mission staff are also interested in recording the tourism sector. This research will focus on examining Garut's economic and tourism development and Global connections in the zending Nederlandsche Zendingsvereeniging (NZV) records. This study uses the historical method using observation and secondary data, consisting of four stages: Heuristics, Critique of Interpretation, and Historiography. The study results stated that Garut made many foreigners live in this region. The progress of transportation built by the Dutch East Indies government had opened the door for tourism development in Garut. The natural beauty of Garut has invited many tourists to visit this area. This tourist visit has grown the new business in the Garut area, namely the construction of various tourism facilities such as hotels, tourism agents, and books containing tourism information in Garut. The following discussion and managerial implications are identified based on empirical findings.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".