Bibliographic record
Abstract
Bushy (2000) points out that “nursing practice in rural environments are very similar in Canada, the United States, and Australia” (p. 236). I think we can now add Japan to that list of countries in which rural nursing has similar characteristics. I recently returned from the island of Honshu in Japan and had the good fortune to meet and discuss rural nursing with a large group of nurses who work at the nursing school attached to Jichi Medical School. They recently received a mandate from the Japanese government to create the Academy of Rural and Remote Nursing at Jichi and are planning on becoming involved in the ICN rural and remote network that is being established.If you are anything like me, before I went to Japan I found it hard to believe that there would even be areas that are considered rural let alone remote in a country as densely populated as Japan. Much to my surprise I found out that because much of the country is very mountainous there are communities that are as isolated as any remote area in Canada. Interestingly, many of these locations have a similar demographic structure to areas in rural Canada, with the majority of residents being either very young or very old.It never ceases to amaze me that despite language differences, cultural differences and differences in health care systems that rural nurses from various parts of the world have so much in common. During my stay in Japan I was asked to be part of a panel discussion with nurses who work in a variety of rural areas throughout the country. I heard stories about lack of anonymity and familiarity in the community, something that could have happened anywhere in a rural community in Canada. I must say that this identification with other rural nurses regardless of culture or language bodes well for the establishment of an international network that will foster the sharing of ideas and concerns. I also think that it is comforting to know there will be a network of like-minded individuals that share many of the concerns and issues of nurses working in isolation, so ultimately no rural nurses need to feel that they are alone.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".