Despite a century's worth of research, arguments surrounding the question of whether far transfer occurs have made little progress toward resolution. The authors argue the reason for this confusion is a failure to specify various dimensions along which transfer can occur, resulting in comparisons of "apples and oranges." They provide a framework that describes 9 relevant dimensions and show that the literature can productively be classified along these dimensions, with each study situated at the intersection of various dimensions. Estimation of a single effect size for far transfer is misguided in view of this complexity. The past 100 years of research shows that evidence for transfer under some conditions is substantial, but critical conditions for many key questions are untested.

The underrepresentation of women at the top of math-intensive fields is controversial, with competing claims of biological and sociocultural causation. The authors develop a framework to delineate possible causal pathways and evaluate evidence for each. Biological evidence is contradictory and inconclusive. Although cross-cultural and cross-cohort differences suggest a powerful effect of sociocultural context, evidence for specific factors is inconsistent and contradictory. Factors unique to underrepresentation in math-intensive fields include the following: (a) Math-proficient women disproportionately prefer careers in non-math-intensive fields and are more likely to leave math-intensive careers as they advance; (b) more men than women score in the extreme math-proficient range on gatekeeper tests, such as the SAT Mathematics and the Graduate Record Examinations Quantitative Reasoning sections; (c) women with high math competence are disproportionately more likely to have high verbal competence, allowing greater choice of professions; and (d) in some math-intensive fields, women with children are penalized in promotion rates. The evidence indicates that women's preferences, potentially representing both free and constrained choices, constitute the most powerful explanatory factor; a secondary factor is performance on gatekeeper tests, most likely resulting from sociocultural rather than biological causes.Keywords: sex differences, spatial ability, mathematics, family versus career trade-offs, women in science Supplemental materials: http://dx.doi.org/10.1037/a0014412.supp By 2001, women were earning 48% of bachelor's degrees (National Science Foundation, 2007) and 29% of PhD degrees (Hill & Johnson, 2004) in mathematics, representing enormous increases over the prior 30 years. Women's representation among editorial boards in science and awards panels similarly increased (Nelson & Brammer, 2008). These changes are evidence of the strength of cultural factors in determining such outcomes, because biology has not changed over this period. Despite this progress, women's representation among PhD degree holders has not coincided with proportional faculty appointments: Women earned 31.3% of chemistry PhD degrees between 1993 and 2003 but in 2002 were hired for only 21.5% of assistant professorships. Similar disparities exist for new faculty appointments in physics, engineering, and mathematics. In 1976 women represented only 7.5% of the faculty in physical sciences and less than 1% in engineering (Dearman & Plisko, 1979). By 2006 the percentage had increased to 16%-25%, but the hiring of assistant professors in these fields has not been proportional to female PhD pools. This hiring disparity extends beyond math-intensive fields.Even in less math-intensive fields, such as cellular and molecular biology, fields in which women obtain 46% of all PhD degrees, women disproportionately drop out at multiple points. The picture is the same across many science fields: Women are not being hired as assistant professors at the ra...

This research investigates the development of transferable-"adaptive"-expertise. The study contrasts problem-solving performance of two kinds of experts (business consultants and restaurant managers) on novel problems at the intersection of their two domains, as well as a group of novices (non-business undergraduates). Despite a lack of restaurant experience, consultants performed better than restaurant managers and undergraduates, even though the problems concerned a restaurant. Process measures suggest this was due to the use of more theoretical reasoning. Analyses show this resulted from differences in work experience and not other factors (e.g., education). We discuss aspects of experience that might be responsible for development of theoretical understanding and, thus, expertise that transfers to novel problems. One possible explanation, consistent with existing research from multiple approaches, is that to transfer to novel problems, experience must include substantive variability. The social context of learning may also play a role. Some argue that learning does not transfer to novel situations, and therefore that education should focus on teaching the precise knowledge that will be needed later (Detterman, 1993). However, educators cannot predict exactly what individuals will need to know in a rapidly changing world. Thus many problems faced, at work and elsewhere, will necessarily be new and unfamiliar. How can performance on such novel problems be enhanced, that is, how can transferable or so-called "adaptive" expertise (Hatano, 1982) be developed? several anonymous reviewers for helpful comments on previous versions of this article; Laura Eselius, Amy Leahy, Jai Sweet, and Jack Young for painstaking help with coding; Cara Olsen for invaluable help with statistical issues; and the participants and "super-exper t" judges for giving freely of their time.

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