MORE THAN LONELINESS? ALTERNATIVE PATHWAYS TO, AND OUTCOMES OF EXCLUSION FROM SOCIAL RELATIONS FOR OLDER PEOPLE
Bibliographic record
Abstract
The most commonly cited marker of exclusion from social relations is loneliness. However, other outcomes from pathways to social exclusion from social relations that may be equally as important to the individual or society, but are less well documented than loneliness. In a theoretical model developed by the working group on exclusion from social relations that is part of the European Cost Action 15122 Reducing Old-Age Social Exclusion: Collaborations in Research and Policy (ROSEnet), the distal outcomes of well-being (e.g. quality of life, life satisfaction, loneliness and belonging); health and functioning; social opportunities and social cohesion are conceptualized as emergent products of a system, in which individual risks, community, environment and macro-structures (governmental policies, values and normative beliefs) are inextricably connected to objective and subjective experiences of exclusion from social relations. The presentations – from the UK, Belgium, Canada and New Zealan - explore the trajectories to exclusion from social relations taking into account the influence of caregiving (Keating et al) and material resources (Waldegrave et al) on the quantity and quality of social relations, psychological resources that may moderate the influence of exclusion on outcomes (De Donder et al), and belonging, social cohesion (Winter & Burholt) and life satisfaction as alternative outcomes (to loneliness) from exclusion. The symposium will start with a brief introduction to the ROSEnet theoretical model of exclusion from social relations. This will be followed by the series of presentations that describe alternative pathways using qualitative, quantitative and mixed methods.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".