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Record W4388996555 · doi:10.1016/j.heliyon.2023.e22835

Exploring the China-Pakistan economic corridor project performance during Covid-19 pandemic

2023· article· en· W4388996555 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBelt and Road Initiative
Canadian institutionsUniversity of Guelph
FundersKing Saud UniversityCalifornia Postsecondary Education Commission
KeywordsPandemicChinaDeveloping countrySocioeconomic statusBusinessEconomic impact analysisEconomic growthCoronavirus disease 2019 (COVID-19)Political scienceEconomicsMedicineEnvironmental healthDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The outburst of the coronavirus into the global arena, first as a respiratory disease and later as a worldwide pandemic and health emergency, pushed the world economic order into complete turmoil and aftermath, posing severe challenges to the financial stability of developing countries like Pakistan. The temporary suspension of economic activities worldwide has resulted in significant disruptions to international supply chains, leading to substantial delays in implementing infrastructure projects associated with the China-Pakistan Economic Corridor (CPEC). The pandemic has further hindered CPEC progress. Building mega-projects, such as the CPEC, is crucial in determining the economic stability of a nation such as Pakistan. Nevertheless, it is essential to consider that the implementation of infrastructure projects can be subject to delays due to the COVID-19 lockdown and travel restrictions. However, it is worth noting that there needs to be more scholarly research available examining the ongoing progress and performance of CPEC projects from a particular perspective. This study aims to assess the impact of the COVID-19 lockdown policy and travel restrictions on CPEC project performances by highlighting the role of socioeconomic and infrastructure development factors. The study will shed light on numerous causes of concerns in project development phases and provide policy recommendations to help CPEC officials reduce project losses and better survival in the event of extreme uncertainty. The data were collected through an online survey from all over Pakistan using self-administered questionnaires with 570 responses from CPEC employees, officials, and professors from management and economic departments. The structural equation modeling (SEM) technique analyzes the problem mentioned above. As per the results of this study, it is evident that the COVID-19 lockdown policy and travel restrictions have a detrimental effect on the construction of the CPEC project. Moreover, it has been observed that the socioeconomic and infrastructure development associated with the CPEC has a notable impact on the performance of the CPEC projects. This paper aims to provide valuable insights to policymakers by examining the management of the COVID-19 pandemic from the perspective of the CPEC.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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.

Opus teacher head0.196
GPT teacher head0.300
Teacher spread0.104 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it