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Record W4411456649 · doi:10.3390/admsci15060236

Fostering Antifragility: What Policymakers Should Know About Individual Resilience in Romania

2025· article· en· W4411456649 on OpenAlexafffund
Călin Vâlsan, Elena Druică, Paul Dragos Aligică

Bibliographic record

VenueAdministrative Sciences · 2025
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsBishop's University
FundersUniversitatea din BucureștiUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si InovariiBishop's University
KeywordsPsychological interventionPerceptionResilience (materials science)Community resiliencePsychologyPsychological resilienceSocial psychologyComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.156
GPT teacher head0.501
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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