C-28 Raven’s Progressive Matrices: Validation of a Short Form
Bibliographic record
Abstract
Abstract Objective The Raven’s Standard Progressive Matrices (RSPM) is a 60-item measure of non-verbal abstract reasoning. The length of the RSPM presents a potential barrier to its use. Consequently, Bilker et al. (2012) identified a 9-item short form (RSPM-SF). The purpose of this study is to (a) provide descriptive statistics for the RSPM-SF from a non-patient sample, and (b) validate the RSPM-SF by exploring correlations with congruent and divergent cognitive measures. Method Twenty men and 23 women, aged 55 to 83 (M = 67.79), completed a test battery that included the SPM-SF and global, memory, verbal, and executive measures. Results The mean score for the RSPM-SF was 4.40 (median = 4, mode = 4, SD = 1.92). RSPM-SF correlated best with the Montreal Cognitive Assessment (r = .548, CI: .297 to .729) and poorest with letter fluency (r = .065, CI: -.456 to .127). Correlations with executive measures ranged from a low of .308 (Tower Test; CI: .019 to .549) to a high of .470 (Trail Making Test Part-B; CI: .197 to .675). The average correlation with executive scores was .412. Average correlation with learning (both verbal and non-verbal) was .435, and with recall was .296. Conclusions RSPM historically was viewed as a non-verbal global estimate of cognitive ability. Present findings support using the RSPM-SF as a global measure, as it correlated well with both verbal and nonverbal, and executive and memory tests. Descriptive data suggested that the RSPM-SF items ranged from easy to difficult.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".