Towards a reliable measure of motor working memory: revisiting Wu and Coulson's (2014) movement span task
Bibliographic record
Abstract
Some researchers have argued that motor working memory is relatively independent from visuospatial working memory and underlies the learning and processing of motor tasks, like gesture comprehension. To allow systematic testing of these claims, Wu & Coulson 2014 Psychol. Sci. 26 , 1717–1727. ( doi:10.1177/0956797615597671 ) proposed a novel measure of motor working memory, the movement span task. Some studies have reported that the movement span task has a high degree of validity. The purpose of the present study was to attempt to replicate Wu & Coulson 2014 Psychol. Sci. 26 , 1717–1727. ( doi:10.1177/0956797615597671 ) in the following ways: (1) the high correlation between movement span and movement recall scores and (2) the lack of correlation between the movement span task on the one hand and visuospatial and verbal working memory on the other. In the present study, we found a high correlation between the movement span and recall scores as well as most measures of visuospatial memory. However, the size of these correlations was similar to that reported by Wu and Coulson, suggesting that the significance may be related to sample size. In other words, motor working memory may be weakly related to visuospatial memory. By contrast, there were weak correlations between the movement span task and verbal memory. In sum, we found the same pattern of results observed by Wu & Coulson 2014, 1717–1727. ( doi:10.1177/0956797615597671 ).
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".