Targeting Social Support: A Network Assessment of the Convoy Model of Social Support
Bibliographic record
Abstract
ABSTRACT One of the most influential applications of the concepts, methods and measures of social network analysis to the study of the social support transactions of older adults is the convoy model of social support. We draw on recent debates in network methodology to provide an assessment of the convoy model that explores the role of weak ties in the support networks of older adults. The social networks generated by the target diagram which operationalizes the convoy model display the structural and functional characteristics set out in its theoretical arguments. But not all of the ties constituting these networks are conduits of social support and, more importantly, these social networks do not include all supporting and supported others. The target diagram identifies core support networks; therefore, support flowing through weak ties is missed when it is used to set the boundaries of support networks. Expanding our picture of the support networks of older adults to take systematic account of weak ties and the emotional aid, instrumental assistance, and companionship that flow through them will enhance the effectiveness of support interventions that target older adults.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".