Bibliographic record
Abstract
본 연구는 Rowe와 Kahn(1997)이 제시한 성공적 노화의 개념 발달의 근간과 그 개념의 틀을 고찰하고, Rowe와 Kahn의 성공적 노화 개념이 한 개인이 속해있는 문화적 배경을 고려하지 않는 한계를 가지고 있음을 주장한다. 캐나다의 이뉴잇족(Inuit), 보츠와나의 산족(!Kung) 및 홍콩의 중국인을 대상으로 수행한 인류학 연구들에 대한 검토를 통해서, 성공적 노화에 대한 이해와 의미 부여가 문화적 배경에 따라 다름을 확인하였고, Rowe와 Kahn의 성공적 노화 개념으로는 설명될 수 없는 부분이 있음을 밝혔다. 이에 본 연구에서는 Rowe와 Kahn의 성공적 노화 개념을 수정·보완하여 기존 개념의 틀이 지녔던 문화적 한계를 극복할 수 있는 방안을 제시하고, 본 연구의 정책적, 실천적 함의를 제시하였다.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".