CHINA’S EXTRA- AND INTRA-ASIAN LINER SHIPPING CONNECTIONS, 1990-2000
Bibliographic record
Abstract
The growth of China’s economy during the 1990s has both shaped and reflected changes in the span and function of the country’s shipping connections both within Asia and with the rest of the world. Although sea-land developments within China have been studied, less attention has been paid to the wider global implications stemming from the transformation of the country’s maritime geography during a decade of further market reforms and greater integration into the world economy. Consequently, there is a need to comprehend how China’s state-owned shipping industry has been reorganized during the 1990s to meet the new requirements, with special reference to the country’s liner shipping connections between and within Asia respectively. More purposely, these topics are addressed by examining changes in the organization, approach and set of connections of the state-owned China Ocean Shipping (Group) Company (Cosco) and its post-1993 offshoot COSCO Container Lines Company Ltd (Coscon). This review provides a springboard for a detailed analysis of shifts in both extra- and intra-Asian shipping patterns between 1990 and 2000 and consideration of their strategic implications. Finally, short-sea shipping is defined and the phenomenon’s operational strengths and weaknesses discussed.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".