A Comparative Study of Rural Clinics in Remote Islands and Inland Areas
Bibliographic record
Abstract
The social and professional isolation of physicians remains an important issue in rural areas. However, few studies have investigated the involvement of geographic factors in the isolation. This study investigates rural public clinics in inland and remote island locations and attempts to objectively compare the isolation of these physicians. A mailed questionnaire was sent to rural clinics where graduate physicians from Jichi Medical School were working in 1994 and 1995. Among the 198 clinics with one or more full-time physicians, 185 (93 percent) responded to the inquiry. Geographic and demographic factors of the communities were compared between 43 clinics located in remote islands and the other 142 rural inland clinics. Rural clinics in remote islands have smaller subject populations, fewer part-time physicians, a longer journey to the nearest city, and a longer distance and travel time to the base hospital than rural inland clinics. Physicians in remote island clinics had less medical training and are more isolated than other physicians. More than half of the clinic physicians in remote islands have no regular training schedule, in contrast to less than a quarter of the inland clinic physicians. Almost all clinics (97.7%) in remote islands do not have a part-time physician, whereas about 20 percent of the rural inland clinics do. Physicians in remote island clinics are more socially and professionally isolated than those in inland clinics. Strategies to reduce these problems should be given priority in rural health policy and measures tailored to rural clinics in remote islands.
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.
How this classification was reachedexpand
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".