Framing of China Pakistan Economic Corridor (CPEC) in Elite Press of India and Afghanistan (2015-2017)
Bibliographic record
Abstract
$1 trillion Belt Road Initiative (BRI)’s China-Pakistan Economic Corridor (CPEC) component is a dimensional shift in Sino-Pak relations and a conception of shared future being heralded as the game changer for Pakistan as well as for the whole region. As a nodal part of the China’s ambitious Belt & Road Initiative that envisage to improve connectivity on transcontinental scale by connecting China to Central and Eastern Europe, the Middle East and Africa, the CPEC has come under attention of international media, policy makers, economists and academicians. This study discusses the framing of CPEC in press of India and China. India being territorial neighbors and China being the investor shares certain interests, reservations and apprehensions related to CPEC. Two English newspapers from China (China Daily & Global Times) and India (Indian Express & The Hindu) were selected and all the news and editorials related to CPEC were analyzed for the period of 2015-2017. Finding reveals that India’s press is covering CPEC more in terms of strategic and conflict perspective rather than infrastructure and connectivity aspects. However, the Chinese press covers CPEC in broader context of BRI and globalization hence connectivity, development, strategic value and economic paybacks are the dominant frames. Moreover, framing of CPEC varies over the time in the press of India and China. Study suggests that policy making is needed to reduce the negative stance and communication differences of international press towards CPEC. Findings imply that Pakistan should made efforts to develop better relations with neighboring countries by engaging them with CPEC as a project of development, mutual benefit and regional integration.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".