A Comparison of Computation Span and Reading Span Working Memory Measures’ Relations With Problem-Solving Criteria
Bibliographic record
Abstract
Researchers have operationalized working memory in different ways and although working memory-performance relationships are well documented, there has been relatively less attention devoted to determining whether seemingly similar measures yield comparable relations with performance outcomes. Our objective is to assess whether two working memory measures deploying the same processes but different item content yield different relations with two problem-solving criteria. Participants completed a computation-based working memory measure and a reading-based measure prior to performing a computerized simulation. Results reveal differential relations with one of the two criteria and support the notion that the two working memory measures tap working memory capacity and other cognitive abilities. One implication for theory development is that researchers should consider incorporating other cognitive abilities in their working memory models and that the selection of those abilities should correspond to the criterion of interest. One practical implication is that researchers and practitioners shouldn't automatically assume that different phonological loop-based working memory scales are interchangeable.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".