An Analysis of the Factors That Influence Elders’ Choice of Location and Housing
Bibliographic record
Abstract
This study was aimed at determining the pull and push factors that influence elders' choices of housing and location. The study sample consisted of 150 seniors aged 60 years and older. The participants were selected by using “snowball sampling technique" and were included in a survey. It was found that the rate of participating elders who did not want to move from their current houses was higher than those who did. The rate of females who did not want to move was higher than that of males (p<0.001). The study results revealed that the most important push factor for elders who moved or considered moving was making plans for the place they wanted to live for the rest of their lives. The mean score of males at this point was found to be higher than that of the females (p<0.001). The main pulling factor among elders who wanted to stay in their houses was the feeling of security. The mean score of females at this point was higher than that of males (p<0.01).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".