Bibliographic record
Abstract
This research tried to provide basic data to the social support strengthening plan for it investigated whether the social support reached any effect on the psychological well-being of the rural elderly, or not increasing the psychological well-being of the rural elderly. For this purpose, this research classified the social support level which the rural elderly is late into the family support, relative support, and public support according to the social supporter and looked into. And it classified the rural elderly psychological well-being level into the positive well-being and negative well-being and looked into the first. Second, the difference of the social support according to the population sociology characteristic and psychological well-being were looked into. Third, in the preceding research, after controlling the age, confirmed as the factor having an effect on the social support of the rural elderly and psychological well-being monthly income, and health condition, the relatively influence that family support, relative support, and public support reaches to the psychological well-being of the rural elderly was looked into. In this research, the survey was performed for 170 old peoples more than the lives in Kyongsangbuk-do Chungdo-gun quarter age of 65. The investigation which supplemented and which it looks at from September 10th in 2011 until September 24th was performed. The total 190 part of questionnaires was distributed and 170 parts except was insincere or is not completed 20 parts of answer were used for the final analysis. Summarizing the result, it is obtained from this research, it is like the next. First, the level of the social support shows in this order-family support, relatives support, public supports. Namely, the rural elderly recognize the families support highest, on the other hand, recognjze the public support lowest. The social support of the rural elderly shows negative well-being higher than positive well-being. It shows that two dimension have negative relationship. Second, the result of analyze the difference of the social support according to the population sociology characteristic of the rural elderly and psychological well-being are as follows. First, as the age was low if we looked at the social support, the rural elderly recognized the whole social support and family support and relative support. And high the family support was high recognized as the monthly income was high. The more the age was high if we looked at the psychological well-being, the negative well-being of the psychological well-being was exposed to be high recognized as the health condition was bad. Third, in case the more the result of looking into the effect that the social support of the rural elderly reaches to the psychological well-being and health condition were similar, the rural elderly psychological well-being level t was high, the positive well-being of the psychological well-being which the rural elderly realizes as the official support was high showed high. In addition, the more the rural elderly psychological well-being level was low in case the monthly income was similar, the negative well-being of the psychological well-being which the rural elderly recognizes as the official support was low was shown up to be high. The theoretical, political, and practical undertone was presented based upon this kind of research result.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".