Assessing port governance models: process and performance components
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.
Bibliographic record
Abstract
This paper develops a conceptual framework that integrates various relevant port performance components in a way that can be used for a comprehensive port evaluation and adjustment of existing port governance models. The paper presents a synthesis of the literature on port governance models and port performance, arguing that the process of change is a dynamic one, and that the performance outcome of a reform process influences the next round of reforms. It also explores the potential for decomposing performance into two different, although related, port performances components, namely efficiency and effectiveness. Bringing into the analysis concepts like the need to integrate users’ satisfaction in port performance assessment, the paper explores the content of each of these components and their relationship. This discussion, along with empirical evidence provided by port authorities, leads to the conclusion that governance decisions, both at firm and government levels, are largely based on a very limited assessment of port performance. The effectiveness of port reform is largely neglected, with user perspectives not being an integral part of an effort to improve performance by the port or as feedback to assess the effectiveness of the governance model imposed by the government's port policy.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it