The Joint Arabic Investments Role at Aqaba Special Economic Zone: Marsa Zayed as a Model
Bibliographic record
Abstract
The study addressed the role of Arabic investments in Aqaba special economic zone (ASEZ), and tried to answer the following questions: are the necessary potentials and features available in (ASEZ) to provide an attractive investment climate for the Arabic investments, what is the level of policies effectiveness for improving the investment climate in (ASEZ) to attract the Arabic investments, what is the level of guarantees effectiveness provided by (ASEZ) to encourage Arabic investments, and what is the level of investment privileges and facilities, related to the investments provided by (ASEZ) to attract the Arab investment to it. Data were collected through one study tool that consisted of 30 paragraphs by using Likert fifth scale. Study importance comes from its benefit to decision makers at (ASEZ) to avoid some of the pitfalls and barriers that face the investment in it, where the descriptive analytical approach was used to calculate the arithmetic means, standard deviations, percentages, and T-test on paragraphs of the questionnaire that was distributed by the simple random survey method. Study results showed the existence of distinctive characteristics within the investment climate at (ASEZ), and also concluded that (ASEZA) plays a big role in attracting Arabic investments to Aqaba, the study in return arrived to the existence of some barriers that limit the Arabic investments attraction to Aqaba, the most important of those are: management problems, multiple decision making parties, bureaucratic, and routine. The study recommended to reformulate operation of the united investment window, in a way that makes it a role model, to repair the internal house of government institutions and agencies dealing with investment, entrepreneurship or projects, and train staffs to facilitate the procedures offers for foreign investors, which encourage them to establish their projects there and improve the image of Jordan as an attractive country for investment and investors.
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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 | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".