China Pakistan Economic Corridor (CPEC): International Media Reporting and Legal Validity of Gilgit-Baltistan
Bibliographic record
Abstract
New Silk Road Initiative is known as Belt and Road Initiative (BRI), an initiative which connect the China to the world for establish a free trade zone. China Pakistan Economic Corridor (CPEC) is one of the mega project of BRI that strengthen the relationship between Pakistan and China. It was started with the initial value of $46 billion for the development of transportation, infrastructure, and energy projects in Pakistan which has reached to $62 billion now. CPEC projects are going to open a new door of progress in Pakistan and also getting an attention of international media to highlight the opportunities and challenges of these ongoing projects. The aim of this study is to observe the international media reporting about the CPEC by examining the international news which was reported in the following international newspapers regarding CPEC, such as Dawn News (Pakistan), Global Times (China), Times of India (India) and BBC News (UK). News reported from January 2018 to June 2018 has the part of my study and tried to find out that the way of international media to shatter the news and what are the differences and similarities among the news reporting. The study has also discussed and clarified the legal territorial right of the regions of the CPEC, especially the Gilgit-Baltistan.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".