ACTIVE PARTICIPATION OF OLDER ADULTS AT POLITICAL RALLIES AS A SOURCE OF RESILIENCE: THE CASE OF THE ISRAELI PROTEST
Bibliographic record
Abstract
Abstract The governing Israeli coalition suggested on Dec 2022 a reform plan that would fundamentally alter the system of checks and balances within Israeli society. According to law experts, the plan would effectively end liberal democracy in Israel. This turn of events sparked the largest protest movement in the 75year history of Israel. The current situation is unparalleled, and the mental health costs appear to be significant. However, the toll on older adults has not been directly examined yet. The breadth of the protest movement is remarkable. A July 2023 poll conducted by the Israel Democracy Institute estimated that almost a quarter of Israeli citizens had participated at a protest action at least once. It was primarily through participation at large rallies held weekly across the country - one of the main symbols of the protest movement. Interestingly, the survey reported a 37% participation rate among older adults, the highesy participation rate among all tested age groups. Since older Israelis are members of the founding generation of the state, their participation is not surprising. They feel threatened as their way of life and heritage are at risk. In the current study, we conducted a survey that examined mental health indices among older Israelis. Specifically, we wanted to test whether active participation at the protest could serve as a source for resilience in older age. Unfortunately, political turmoil is not unique to Israel. Thus, we hope that our findings could assist practitioners globally.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".