Measuring accessibility and island development in Ambon City
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
Island studies has thus far mostly focused on the limitations, isolation and marginality of island communities. However, recent research into island cities, or urban island studies, provides an analytic lens or research perspective that can be used to understand an island’s diversity and to encourage researchers to identify island characteristics that have an impact on the function of cities and population centers on islands. One of the factors that inhibit the development of island cities is the limited availability of land area and resources, causing island city regions to depend on other regions to fulfill the population’s needs and provide basic services to the population, which puts islands in a vulnerable position because of transportation accessibility problems. This study was conducted using the Transit Opportunity Index (TOI) method to observe the relationship between transportation accessibility and economic growth in island city regions. The result of the analysis showed that transportation accessibility indirectly affects economic growth in every district/city in Maluku Province. Sea transportation accessibility better illustrates the condition of transportation accessibility of Ambon City and other districts/cities in Maluku Province compared to sea and air transportation accessibility.
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 | 0.001 | 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 | 0.001 |
| 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