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      Gender Differences in Familiar Face Recognition and the Influence of Sociocultural Gender Inequality

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          Abstract

          Are gender differences in face recognition influenced by familiarity and socio-cultural factors? Previous studies have reported gender differences in processing unfamiliar faces, consistently finding a female advantage and a female own-gender bias. However, researchers have recently highlighted that unfamiliar faces are processed less efficiently than familiar faces, which have more robust, invariant representations. To-date, no study has examined whether gender differences exist for familiar face recognition. The current study addressed this by using a famous faces task in a large, web-based sample of  > 2000 participants across different countries. We also sought to examine if differences varied by socio-cultural gender equality within countries. When examining raw accuracy as well when controlling for fame, the results demonstrated that there were no participant gender differences in overall famous face accuracy, in contrast to studies of unfamiliar faces. There was also a consistent own-gender bias in male but not female participants. In countries with low gender equality, including the USA, females showed significantly better recognition of famous female faces compared to male participants, whereas this difference was abolished in high gender equality countries. Together, this suggests that gender differences in recognizing unfamiliar faces can be attenuated when there is enough face learning and that sociocultural gender equality can drive gender differences in familiar face recognition.

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          Cross-national patterns of gender differences in mathematics: a meta-analysis.

          A gender gap in mathematics achievement persists in some nations but not in others. In light of the underrepresentation of women in careers in science, technology, mathematics, and engineering, increasing research attention is being devoted to understanding gender differences in mathematics achievement, attitudes, and affect. The gender stratification hypothesis maintains that such gender differences are closely related to cultural variations in opportunity structures for girls and women. We meta-analyzed 2 major international data sets, the 2003 Trends in International Mathematics and Science Study and the Programme for International Student Assessment, representing 493,495 students 14-16 years of age, to estimate the magnitude of gender differences in mathematics achievement, attitudes, and affect across 69 nations throughout the world. Consistent with the gender similarities hypothesis, all of the mean effect sizes in mathematics achievement were very small (d < 0.15); however, national effect sizes showed considerable variability (ds = -0.42 to 0.40). Despite gender similarities in achievement, boys reported more positive math attitudes and affect (ds = 0.10 to 0.33); national effect sizes ranged from d = -0.61 to 0.89. In contrast to those of previous tests of the gender stratification hypothesis, our results point to specific domains of gender equity responsible for gender gaps in math. Gender equity in school enrollment, women's share of research jobs, and women's parliamentary representation were the most powerful predictors of cross-national variability in gender gaps in math. Results are situated within the context of existing research demonstrating apparently paradoxical effects of societal gender equity and highlight the significance of increasing girls' and women's agency cross-nationally.
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            Is the Web as good as the lab? Comparable performance from Web and lab in cognitive/perceptual experiments.

            With the increasing sophistication and ubiquity of the Internet, behavioral research is on the cusp of a revolution that will do for population sampling what the computer did for stimulus control and measurement. It remains a common assumption, however, that data from self-selected Web samples must involve a trade-off between participant numbers and data quality. Concerns about data quality are heightened for performance-based cognitive and perceptual measures, particularly those that are timed or that involve complex stimuli. In experiments run with uncompensated, anonymous participants whose motivation for participation is unknown, reduced conscientiousness or lack of focus could produce results that would be difficult to interpret due to decreased overall performance, increased variability of performance, or increased measurement noise. Here, we addressed the question of data quality across a range of cognitive and perceptual tests. For three key performance metrics-mean performance, performance variance, and internal reliability-the results from self-selected Web samples did not differ systematically from those obtained from traditionally recruited and/or lab-tested samples. These findings demonstrate that collecting data from uncompensated, anonymous, unsupervised, self-selected participants need not reduce data quality, even for demanding cognitive and perceptual experiments.
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              Recollection and familiarity: examining controversial assumptions and new directions.

              It is well accepted that recognition memory reflects the contribution of two separable memory retrieval processes, namely recollection and familiarity. However, fundamental questions remain regarding the functional nature and neural substrates of these processes. In this article, we describe a simple quantitative model of recognition memory (i.e., the dual-process signal detection model) that has been useful in integrating findings from a broad range of cognitive studies, and that is now being applied in a growing number of neuroscientific investigations of memory. The model makes several strong assumptions about the behavioral nature and neural substrates of recollection and familiarity. A review of the literature indicates that these assumptions are generally well supported, but that there are clear boundary conditions in which these assumptions break down. We argue that these findings provide important insights into the operation of the processes underlying recognition. Finally, we consider how the dual-process approach relates to recent neuroanatomical and computational models and how it might be integrated with recent findings concerning the role of medial temporal lobe regions in other cognitive functions such as novelty detection, perception, implicit memory and short-term memory. © 2010 Wiley-Liss, Inc.
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                Author and article information

                Contributors
                degutis@hms.harvard.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                29 November 2019
                29 November 2019
                2019
                : 9
                : 17884
                Affiliations
                [1 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Psychiatry, , Harvard Medical school, ; Boston, MA USA
                [2 ]Boston Attention and Learning Laboratory, VA Boston Healthcare, Jamaica Plain Division, 150 S Huntington Ave., Boston, MA USA
                [3 ]ISNI 0000 0004 1936 9561, GRID grid.268091.4, Department of Psychology, , Wellesley College, 106 Central Street, ; Wellesley, MA 02481 USA
                [4 ]ISNI 000000041936754X, GRID grid.38142.3c, Harvard Medical School, , Harvard University, 401 Park Drive, Suite, ; 504W Cambridge, MA USA
                [5 ]ISNI 0000 0000 8795 072X, GRID grid.240206.2, Institute for Technology in Psychiatry, McLean Hospital, ; Belmont, MA USA
                Article
                54074
                10.1038/s41598-019-54074-5
                6884510
                31784547
                beaee4cb-945b-4639-8ee9-e3f779f912e5
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 August 2019
                : 7 November 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000053, U.S. Department of Health & Human Services | NIH | National Eye Institute (NEI);
                Award ID: R01EY026057
                Award ID: R01EY026057
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Eye Institute (NEI)
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                human behaviour,social behaviour
                Uncategorized
                human behaviour, social behaviour

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