THE IMPACT OF FOREING DIRECT INVESTMENT IN THE PETROLEUM SECTOR ON THE EGYPTIAN ENVIRONMENT
Bibliographic record
Abstract
Countries all over the world are racing to attract as much foreign direct investment (FDI) as possible due to its crucial impact on the economic development projects in the hosting countries. If these countries could well choose their economic projects and foreign partners, FDI could fill up the gap of limited resources and possibilities, increase the investment base, and help making the best use of the available natural resources for the hosting countries. Furthermore, FDI is an effective tool to transfer and use new technologies, as well as create new jobs in the hosting countries. Petroleum sector is one of the most important investing sectors with its huge directed investment whether for searching, exploring or extracting processes. Moreover, petroleum has a significant impact on the environment, as it emits contaminated waste while being produced. Thus, extracting petrol is an expensive process and -in some cases- harmful to the environment. The current research aims to study the impact of FDI in petroleum sector on the environment and to study the advantages and disadvantages of FDI in petroleum sector. To achieve that, analytical method based on the extrapolation method was used through gathering and analyzing the required data. Data was collected from CAPMAS (Central Agency for Public Mobilization and Statistics) and reports of the Central Bank of Egypt during the period of 2008 and 2016. The collected data was statistically analyzed through “SPSS” software. Results show that FDI in petroleum sector has a significant impact on the environment due to the harmful emissions resulted from searching, exploring and extracting processes; protecting the environment leads to huge cost as petrol production has the highest portion of the total FDI comparing with other sectors. Furthermore, this cost increases as FDI increases in spite of the exerted efforts. Researchers recommend to do more efforts in the petroleum sector to reduce the pollution resulted from FDI, spend more money on researches and development processes as well as use modern technologies that reduce the emissions of petroleum sector production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".