Facility Centers in Rural Areas: Concept, Development, Effect on Habitational Accessibility and Facility Crowdedness, and Policy Strategies for Resource Allocation
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 article discusses the concept of facility center development by identifying locations for colocating multiple facility types so as to access several facilities at a single location. This concept maximizes accessibility and reduces travel costs for individuals with multiple trip purposes. The appropriateness of facility center locations are evaluated with two parameters: (1) habitation accessibility to facility centers using the two-step-floating-catchment-area (2SFCA), method, and (2) facility center crowdedness using the inverted two-step-floating-catchment-area (i2SFCA) method. This study uses both 2SFCA and i2SFCA methods concurrently to get perception of quality of service provided and received. Considering two facilities such as a health care center and a high school for spatial planning of facility centers, the proposed methodology is analyzed for two cases. In the first case, it is assumed that no facility exists in the study area and in the second case, the existing locations of health care centers and high schools are considered for analysis. The proposed methodology is applied in Jhunjhunu—a district in Rajasthan, India—as a case study. The discussed policy strategy would help with resource allocation in a phased manner for new facility development or capacity augmentation of existing facilities, and thus would improve the quality of rural citizens’ lives.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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