CPEC: Threat or Opportunity Protecting Local Industry through Infant Industry Theory Framework
Bibliographic record
Abstract
China-Pakistan Economic Corridor is a massive investment initiative by China with a whopping amount of $62 billion. The project includes various short term and long term plans for energy, infrastructure, IT and R&D projects. The completion of short term plans by the end of 2018 and initiation of long term projects demand a comprehensive analysis as the project of CPEC presents both threat and opportunities for local producers. The threats include competition for local producers from innovative products of China and technological and managerial superiority of Chinese companies over Pakistani industry. However, the domestic producers feel more optimist as energy and infrastructure projects, and induction of new technology would benefit the business sector in Pakistan. The purpose of this study is to explore and identify the possible threats and opportunities considering “Infant Industry Theory” as an analytical framework. A qualitative and quantitative research methodology is employed and the data is gathered from 20 divergent and potential sector of SMEs through a close ended survey questionnaire. The likert scale is used to evaluate the opinions of respondents for awareness, challenges; and threats and opportunities of CPEC. The results revealed that SMEs owners are now more aware about the CPEC and its related details while the major challenges for producers were to cope with the low access to finance, unavailability of business and legal advisory services and difficulties in market access. Moreover, the majority of selected respondents consider the project of CPE as an opportunity for their businesses, industry and economy of Pakistan. It is thus concluded that business sector in Pakistan is preparing for CPEC, but with the fact that the required results are not possible till the challenges and concerns of local producers are addressed by the government in appropriate way through effective policies and efficient management. Hence, a detailed policy plan for the local industry specifying CPEC is highly recommended.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".