"CROSS-CULTURAL VALIDATION OF THE RESILIENCE SCALE FOR ADULTS IN THE QUEBEC UNIVERSITY POPULATION"
Bibliographic record
Abstract
In recent years, the concept of resilience has received attention from many researchers, particularly in light of the pandemic (Kontogiannis, 2021;Vindegaard & Benros, 2020).Several studies have sought to map the situation in various countries and compare how nations are coping with this adversity.Resilience is therefore a timely topic and concerns about the methodological aspects associated with cultural comparisons are justified.In this context, the main objective of this dissertation is to contribute to the cross-cultural validation of a widely recognized instrument for measuring resilience; the Resilience Scale for Adults (RSA; Hjemdal et al., 2001) with a sample of 405 Quebec and French speaking students.For comparison purposes, the statistical analyses carried out were based on two measurement models: the classical test theory and the item response theory.Analyses of the factor structure of the instrument show that the six-factor model obtained using exploratory structural equations (ESEM) fits the data collected from the Quebec sample well.The alpha coefficients of the dimensions vary from very good (0.84) to excellent (0.95).These results are comparable to those obtained with other cultural groups by several researchers.The analysis of classic items and that based on Samejima's (1969) graded model show that the majority of the RSA items are effective and useful for evaluating resilience in Quebecers, especially in those with a very low to moderate level of resilience.Five items present less satisfactory indices: three in the Social Competence dimension and two in the Social Resources dimension.All in all, the RSA has satisfactory metric qualities and is an instrument that can be used to assess resilience in the Quebec context.Studies involving direct comparisons between cultures are still needed to support these results.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".