Reliability Generalization as a Seal of Quality of Substantive Meta-Analyses: The Case of the VIA Inventory of Strengths (VIA-IS) and Their Relationships to Life Satisfaction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Reliable test scores are essential to interpret the results obtained in statistical analyses correctly. In this study, we used the Values in Action Inventory of Strengths (VIA-IS) as an example of a widely applied assessment instrument to analyze its metric quality in what is known as reliability generalization (RG). In addition, we conducted a meta-analysis of the correlations between character strengths and life satisfaction to examine the potential relationship between the reliability of test scores and the intensity of these correlations. The overall variability of alpha coefficients supports the argument that reliability is sample dependent. Indeed, there were statistically significant mean reliability differences for scores across the 24 scales, with the highest level of reliability observed for Creativity and the lowest for scores on Self-regulation. Significant moderators such as the standard deviation of the scores and the sample type contribute to understand the high variability observed in the reliability estimation. The second meta-analysis showed that Zest, Hope, Gratitude, Curiosity, and Love were the character strengths that were highly related to life satisfaction, while Modesty and Prudence were less related to life satisfaction. Furthermore, the high heterogeneity between samples might be an indicator of the relationship between the variability of reliability of character strengths' scores and the intensity of their correlations with life satisfaction. Those character strengths with high-potential RG are related or unrelated to life satisfaction, whereas character strengths with less-potential RG showed unstable correlation patterns. The results of both studies point out the role of the relationship between the reliability of test scores and substantive studies, such as Pearson's correlations meta-analysis.
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.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it