What are the Risk Factors of Social Isolation and Loneliness
Bibliographic record
Abstract
This educational PowerPoint presentation is intended to be used as a training resource and can be reviewed individually or as part of a group training session. It will allow you and your staff to review the risk factors that contribute to social isolation and loneliness, and learn about why/how immigration can be a risk factor for social isolation/loneliness. This training module will also encourage you to consider and discuss which risk factors might affect the older adults you work with and consider solutions.\nThis resource is included in the Social Isolation and Loneliness Toolkit, created by the Centre for Elder Research in Oakville ON, Canada. The Toolkit is part of a research project titled “Building Connected Communities: improving Community Supports to Reduce Loneliness and Social Isolation in Immigrants 65+”. The research focused on exploring strategies to effectively reach out to, and support, older immigrants who may be experiencing, or are at risk of experiencing, social isolation and/or loneliness.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".