Dimensional analysis of the 'Belonging component' of quality of life of elderly across varying support.
Bibliographic record
Abstract
A study was undertaken to assess the various dimensions of the 'Belonging component' of the quality of life of elderly (65 years and above) living in various types of support systems.'Belonging component' refers to how one fits in with people and places and is known to strongly impact the quality of life of an individual. The study comprised a sample of 400 subjects from Ludhiana city, equally drawn from four support systems viz., elderly living with sons, living with daughters, living alone, and living in institutions. The sample was further divided over the two sexes. A quality of life profile, senior's version prepared and published by quality of life research unit, University of Toronto, Canada (2000) was administered to measure the 'Belonging component' of quality of life (QOL) of the subjects across various support systems. The 'Belonging component' of the QOL was studied under three dimensions viz., 'Physical belonging' pertaining to how one fits in with the physical aspects of his environment, 'Social belonging' relating to how one fits in with the people around one's life and 'Community belonging' referring to the nexus between an individual and the resources that are typically available to most members of one's community. The study revealed that there were significant gender differentials across different dimensions of the 'Belonging component' of the QOL of aged living across different support systems. It was found that very few elderly females compared to males were enjoying 'Very good quality of life' with respect to the 'Belonging component'. The results revealed that 'Social belonging' dimension was significantly weaker for females living across all support systems except those 'living with daughters'. However, the 'Physical belonging' and 'Community belonging' dimensions were found to be significantly weaker for females 'living alone or in institutions'. Comparatively, the picture was far more encouraging for their male counterparts.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".