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Record W2469427312 · doi:10.1177/1074840716655530

Family Caregiving in Japan

2016· article· en· W2469427312 on OpenAlexaff
Satomi Yamaguchi, S. Robin Cohen, Miyoko Uza

Bibliographic record

VenueJournal of Family Nursing · 2016
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMcGill UniversityJewish General Hospital
FundersJapan Society for the Promotion of Science
KeywordsFeelingConstruct (python library)Value (mathematics)PsychologyPerceptionSocial psychologyQualitative researchSociology

Abstract

fetched live from OpenAlex

Caring culture is a concept embodying the perceptions and caring practices of caregivers, acknowledging the unique role of cultural beliefs in shaping behavior. A qualitative descriptive study with 13 caregivers of adult family members with a cancer diagnosis in Japan was conducted to gain insight into perceptions and experiences surrounding caregiving. Several major categories were identified, representing rarely reported cultural constructs of high cultural value for the Japanese: On-repayment for what the patient has given, Caregiving as performing a socially expected role, Enryo/meiwaku-restraint in asking for help, Family decision making reflecting strong bonds, Omoiyari-empathizing with the patient's feelings, and Inori-praying to myriad gods and ancestors. The Japanese cultural construct of ie (the strong relationship to family lineage and spiritual connection to past and future generations) is helpful in understanding these categories. Invisible yet powerful cultural constructs permeated caregiving practices. Insights from Japanese cultural concepts and beliefs may foster sensitivity and individualized care in diverse settings, cultures, and societies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.148
GPT teacher head0.430
Teacher spread0.282 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations32
Published2016
Admission routes1
Has abstractyes

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