Research Trends Analysis on Port Hinterland Using SNA Method
Bibliographic record
Abstract
In this paper, the research trends of port hinterland from 1990 to 2018 were analyzed periodically using the Social Network Analysis (SNA) method. The data were collected from major academic journals and totally 116 papers were identified for analysis. The results of the analysis showed that in the first period (1990-1999), keywords can be listed as “containerization”, “transport infrastructure” and developed countries related keywords like “Italy”, “Canada” and “Germany”. The results of the second period (2000-2009) were originated from keywords such as “regionalization”, “competitiveness”, “Asian consolidation” and “technology”. In the third period (2010-2018), the results were derived from keywords such as “intermodal transport”, “dry port”, “container” and container related keywords and “shipping” and shipping related keywords. We could see the studies of port hinterland are becoming more systematic and integrated. This study provides some important implications for both academic, and industrial viewpoints, and it is helpful to understand the research concentration.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.037 | 0.039 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".