Gender Development in Gender Diverse Children.

Within "mainstream" developmental science, gender researchers largely study the developmental trajectory of children considered to be "gender-typical", while research housed primarily in psychiatry and clinical psychology often documents the trajectories of gender diverse children. This article aims to bridge the studies of gender diversity and "mainstream" gender development. First, we review literature on the development of four commonly studied subgroups of gender diverse children - children referred to medical clinics because of their gender identity and expression, transgender children, female children with congenital adrenal hyperplasia, and tomboys - highlighting how these gender trajectories do or do not align with modal developmental patterns. We then describe social, cognitive, and biological determinants of gender in light of their implications for understanding diverse gender development. Finally, we note methodological suggestions for future research, with an eye toward better integrating research on gender diversity into "mainstream" gender development research.

Analytic reproducibility in articles receiving open data badges at the journal Psychological Science: an observational study.

For any scientific report, repeating the original analyses upon the original data should yield the original outcomes. We evaluated analytic reproducibility in 25 Psychological Science articles awarded open data badges between 2014 and 2015. Initially, 16 (64%, 95% confidence interval [43,81]) articles contained at least one 'major numerical discrepancy' (>10% difference) prompting us to request input from original authors. Ultimately, target values were reproducible without author involvement for 9 (36% [20,59]) articles; reproducible with author involvement for 6 (24% [8,47]) articles; not fully reproducible with no substantive author response for 3 (12% [0,35]) articles; and not fully reproducible despite author involvement for 7 (28% [12,51]) articles. Overall, 37 major numerical discrepancies remained out of 789 checked values (5% [3,6]), but original conclusions did not appear affected. Non-reproducibility was primarily caused by unclear reporting of analytic procedures. These results highlight that open data alone is not sufficient to ensure analytic reproducibility.