Industrial- or Residential-Dominant Development? A Comparative Analysis of Maritime Industrial Development Areas of Liaoning, China
Bibliographic record
Abstract
This paper adopts a case-comparison method to study the spatial layout features of maritime industrial development areas (MIDAs) in Liaoning, China, in reference to similar projects in other Asian countries including Japan, South Korea and Singapore. Our study focuses on industry-city spatial relationship, land position and proportion, coastline utilization intensity and industrial land organization. We show that supplementary residential and recreational land has primarily occupied the high-quality coastlines, and resulted in limited industrial access to marine resources. Our theoretical and empirical analyses connect this feature to local government finances, purchase restriction policy and an investment-driven surge in demand for coastal residential housing. Many areas now exhibit low utilization of industrial land accompanied by the emergence of “ghost cities” phenomenon, which are critical factors that the policymakers should consider in the future planning of coastal development. Interviews with local developers, housing authority personnel, relocated employees and residents confirm our findings. We conclude with policy recommendations for promoting long-term sustainable development in the coastal area.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".