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Separating bias and sensitivity in judgments of associative memory
1Department of Psychology, Texas Tech University, Lubbock, TX 79409-2051, USA. bill.maki@ttu.edu
Judgments of Associative Memory (JAM) ratings show a high intercept and shallow slope. Experiments manipulating word pair discrimination and rating constraints successfully lowered the intercept but did not alter the slope, suggesting independent control over bias and sensitivity.
Area of Science:
- Cognitive Psychology
- Psycholinguistics
- Memory Research
Background:
- Human associative memory research investigates how people perceive connections between words.
- The Judgments of Associative Memory (JAM) function describes the relationship between perceived word association and objective measures.
- Existing JAM functions exhibit a high intercept and shallow slope, indicating a potential bias in subjective ratings.
Purpose of the Study:
- To investigate methods for reducing the intercept and increasing the slope of the JAM function.
- To determine if the intercept and slope components of the JAM function can be independently manipulated.
- To differentiate between bias and sensitivity components within associative memory judgments.
Main Methods:
- Two experiments were conducted involving word association tasks.
- Experiment 1 utilized discrimination training on word pairs.
- Experiment 2 constrained subjective word association ratings to sum to a constant.
Main Results:
- Both discrimination training and rating constraints significantly reduced the intercept of the JAM function.
- Neither experimental manipulation affected the slope of the JAM function.
- The results suggest that the intercept reflects a manipulable bias, while the slope reflects associative sensitivity.
Conclusions:
- The intercept of the JAM function appears to represent a bias component that can be independently adjusted.
- The slope of the JAM function, reflecting sensitivity to associative strength, remains resistant to the tested manipulations.
- Understanding these independent components offers new insights into the mechanisms of human associative memory.
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