Impact of Tourism Sector on Gross Domestic Product Growth in Jordan
Bibliographic record
Abstract
This study investigates the impact of development of tourism sector on GDP growth rate in Jordan by depending on annual statistics for the period (2010 – 2017); as receipts of tourism sector percentage to exports, arrivals of tourists and expenditures of tourism sector percentage to imports are independent variables, while growth rate of GDP (an indicator of economic growth), is a dependent variable. This paper begins with theoretical studies that analyze the impact of development of tourism sector on GDP growth rate, and empirical studies to analyze this impact. After that, it analyzes the impact of development of tourism sector on GDP growth rate in Jordan by depending on annual statistics for the period (2010 – 2017) by depending on ordinary least squares method by SPSS version. The study finds insignificant impacts of receipts of tourism sector percentage to exports and arrivals of tourists on GDP growth rate in Jordan by depending on annual statistics for the period 2010 to 2017, but there is a negative and significant impact of expenditures of tourism sector percentage to imports on GDP growth rate in Jordan by depending on annual statistics for the period 2010 to 2017. The study recommends decreasing expenditures of tourism sector due to their negative impacts on GDP growth rate.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".