A Pattern of Social Support for Pandemics and Crisis Periods: Vefa Social Support Groups; Türkiye-Isparta Province Example
Bibliographic record
Abstract
In order to prevent the spread of the disease in the Covid-19 pandemic, various restrictions such as curfew, partial shutdowns, or full shutdowns have been taken. These restrictions have also brought to light the importance of social assistance and solidarity. Within the framework of the study, the purpose, structure, and operation of the social support model developed in Türkiye were established to avoid the victimization of individuals who were unable to take the streets and who had no one to help them address their needs. In order to meet the basic needs of citizens aged 65 and older and chronically ill during the pandemic process, Vefa Social Support Groups (VSSG) were formed throughout Türkiye and various demands of a quarter of Türkiye's population were met. While the application in various provinces has been terminated, the VSSG, which continues its activities in the province of Isparta, has been discussed in-depth in the study. It has been observed that Isparta Vefa Social Support Groups (IVSSG) fulfills the demands of citizens in seven different items such as bank transactions, billing transactions, food-market shopping, salary check, drug supply, permission request and other (dress-up and fuel assistance requests, etc.).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".