Fostering Antifragility: What Policymakers Should Know About Individual Resilience in Romania
Bibliographic record
Abstract
Recent studies document a disappointingly low impact of resilience interventions and policies. This prompts us to revisit the formation of perceived individual resilience using a country-representative sample of 1500 adults. Our study explores how this perception is shaped by family resilience, community resilience, and several control variables like age, gender, risk aversion, and the perception of immediate environmental safety. Unlike traditional methods, we employ the PLS-PM methodology and WarpPLS 7.0 software. Our key findings document non-linear dynamics with varying degrees of magnitude, significance, and effect sizes. The three dimensions of family resilience (social trust, shared beliefs and support, and family organization and interaction) are the most significant predictors of community resilience. These non-linear relationships might explain occasional declines in individual resilience, linking our findings to those of previous studies. We contend that resilience policies and interventions are not unlike risk management, and therefore policymakers should be aware of diminishing marginal returns.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".