Tourism Promotion through the Internet (Websites): (Jordan as a Case Study)
Bibliographic record
Abstract
This research paper seeks to study the status of tourism promotion in Jordan, in particular via the Internet, with a future plan to develop this type of promotion based on the needs of the country .The aim of this research paper is to draw conclusions that help to know and understand this type of tourism promotion, And to know how to develop it in Hashemite Kingdom of Jordan to disseminate the maximum information about the Kingdom.This research paper is designed to determine the conditions of websites used in tourism promotion of Jordan, to find out the obstacles that face this type of promotion via websites, and the factors that affect its development .The findings and recommendations implied by this research paper will be presented to decision-makers in Jordan tourism sector to be taken into account. The research paper adopted carefully a survey form which is designed to collect data and information. It is used to know the trends and opinions of the research paper sample. The results showed that the tourism promotion through the Internet helps to increase competition in the prices of tourism, while the website design helps to spread information about the tourism offers. Both sexes consider that the website design as a means helps to ensure the information veracity of tourism offers.The research paper recommended to continue development of the role of tourism promotion through the Internet in spreading information about the tourism offers, so as to achieve the greatest possible benefits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".