Holistic processing refers to the processing of objects as wholes rather than in a piecemeal, part-based fashion. Despite a suggested link between expertise and holistic processing, the role of experience in determining holistic processing of both faces and objects has been questioned. Here, we combine an individual differences approach with an experimental training study and parametrically manipulate experience with novel objects to examine the determinants of holistic processing. We also measure object-recognition ability. Our results show that although domain-general visual ability is a predictor of the ability to match object parts, it is the amount of experience people have individuating objects of a category that determines the extent to which they process new objects of this category in a holistic manner. This work highlights the benefits of dissociating the influences of domain-general ability and domain-specific experience, typically confounded in measures of performance or “expertise.” Our findings are consistent with those in recent work with faces showing that variability specific to experience is a better predictor of domain-specific effects than is variability in performance. We argue that individual differences in holistic processing arise from domain-specific experience and that these effects are related to similar effects of experience on other measures ofmore »
Research Note on the Importance of a Holistic Approach for Population Studies
This research note illustrates the importance of a holistic approach to family demography and children’s well-being. Using the family configurations published in a previous study, we show that a configurational measure of family patterns predicts better the country-level proportion of stunted and wasted children across 75 low- and middle-income countries than 20 single family-related variables, world regions, and the Human Development Index. We contend that demographers need to do a better job of measuring social systems because individuals’ choices are influenced by contexts that are better represented with measures that capture multiple related factors (holistic approach) than with a single variable (analytical approach).
- Award ID(s):
- 1729185
- Publication Date:
- NSF-PAR ID:
- 10340617
- Journal Name:
- Population Studies
- ISSN:
- 0032-4728
- Sponsoring Org:
- National Science Foundation
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