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Record W2122817280 · doi:10.1177/1074840713486872

An Outline of the History of Family Nursing in Japan and the Japanese Association for Research in Family Nursing (JARFN)

2013· editorial· en· W2122817280 on OpenAlexaboutno aff
Kazuko Ishigaki

Bibliographic record

VenueJournal of Family Nursing · 2013
Typeeditorial
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsnot available
Fundersnot available
KeywordsNursingAssociation (psychology)MedicineFamily medicineFamily historyPsychology

Abstract

fetched live from OpenAlex

The term family nursing first came to be known in Japan in 1993 when Chiba University and the University of Tokyo both started offering courses in family nursing. Although the family nursing curriculum at Chiba University was endowed for 5 years, Professor Kazuko Suzuki (who, since retiring from Tokai University as a professor, is currently running her research institute) and Hiroko Watanabe (who is currently directing the Family Care Research Institute) vigorously wrote textbooks and held an international symposium during this 5-year period, in an effort to popularize family nursing research throughout Japan. The symposium invited Professor Wright and Associate Professor Bell from the University of Calgary, and its participants included Professor Michiko Moriyama among others. These were truly the days in which family nursing was being introduced to Japan. Meanwhile, the University of Tokyo was steadily building a foundation for family nursing by hosting an official course taught by Professor Chieko Sugishita. Back then, Kazuko Ishigaki (currently the president of Ishikawa Prefectural Nursing University) was an associate professor and Naohiro Hohashi (presently a professor at Kobe University) was an assistant instructor. This course later had Noriko Yamamoto (presently a professor at University of Tokyo), Nami Kobayashi (presently a professor at Kitasato University), and others as its graduates.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.791
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.180
GPT teacher head0.474
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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