Wendy M. Williams

Women's Underrepresentation in Science: Sociocultural and Biological Considerations

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 womens 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.

Understanding current causes of women's underrepresentation in science

Explanations for womens underrepresentation in math-intensive fields of science often focus on sex discrimination in grant and manuscript reviewing, interviewing, and hiring. Claims that women scientists suffer discrimination in these arenas rest on a set of studies undergirding policies and programs aimed at remediation. More recent and robust empiricism, however, fails to support assertions of discrimination in these domains. To better understand womens underrepresentation in math-intensive fields and its causes, we reprise claims of discrimination and their evidentiary bases. Based on a review of the past 20 y of data, we suggest that some of these claims are no longer valid and, if uncritically accepted as current causes of womens lack of progress, can delay or prevent understanding of contemporary determinants of womens underrepresentation. We conclude that differential gendered outcomes in the real world result from differences in resources attributable to choices, whether free or constrained, and that such choices could be influenced and better informed through education if resources were so directed. Thus, the ongoing focus on sex discrimination in reviewing, interviewing, and hiring represents costly, misplaced effort: Society is engaged in the present in solving problems of the past, rather than in addressing meaningful limitations deterring womens participation in science, technology, engineering, and mathematics careers today. Addressing todays causes of underrepresentation requires focusing on education and policy changes that will make institutions responsive to differing biological realities of the sexes. Finally, we suggest potential avenues of intervention to increase gender fairness that accord with current, as opposed to historical, findings.

Growing up digital.

The Victorian Department of Education and Early Childhood Development [DEECD], Symantec, Cyber Safe Kids and Common Sense Media are currently conducting a pilot collaborative project in which 10 selected schools are trialing a digital citizenship curriculum. This digital citizenship curriculum has been aligned with local/national and international curriculum achievement standards, learning areas, competencies/capabilities. Participating schools will also trial the use of an Incident Response Tool.

Women in Academic Science A Changing Landscape

Much has been written in the past two decades about women in academic science careers, but this literature is contradictory. Many analyses have revealed a level playing field, with men and women faring equally, whereas other analyses have suggested numerous areas in which the playing field is not level. The only widely-agreed-upon conclusion is that women are underrepresented in college majors, graduate school programs, and the professoriate in those fields that are the most mathematically intensive, such as geoscience, engineering, economics, mathematics/computer science, and the physical sciences. In other scientific fields (psychology, life science, social science), women are found in much higher percentages. In this monograph, we undertake extensive life-course analyses comparing the trajectories of women and men in math-intensive fields with those of their counterparts in non-math-intensive fields in which women are close to parity with or even exceed the number of men. We begin by examining early-childhood differences in spatial processing and follow this through quantitative performance in middle childhood and adolescence, including high school coursework. We then focus on the transition of the sexes from high school to college major, then to graduate school, and, finally, to careers in academic science. The results of our myriad analyses reveal that early sex differences in spatial and mathematical reasoning need not stem from biological bases, that the gap between average female and male math ability is narrowing (suggesting strong environmental influences), and that sex differences in math ability at the right tail show variation over time and across nationalities, ethnicities, and other factors, indicating that the ratio of males to females at the right tail can and does change. We find that gender differences in attitudes toward and expectations about math careers and ability (controlling for actual ability) are evident by kindergarten and increase thereafter, leading to lower female propensities to major in math-intensive subjects in college but higher female propensities to major in non-math-intensive sciences, with overall science, technology, engineering, and mathematics (STEM) majors at 50% female for more than a decade. Post-college, although men with majors in math-intensive subjects have historically chosen and completed PhDs in these fields more often than women, the gap has recently narrowed by two thirds; among non-math-intensive STEM majors, women are more likely than men to go into health and other people-related occupations instead of pursuing PhDs. Importantly, of those who obtain doctorates in math-intensive fields, men and women entering the professoriate have equivalent access to tenure-track academic jobs in science, and they persist and are remunerated at comparable rates—with some caveats that we discuss. The transition from graduate programs to assistant professorships shows more pipeline leakage in the fields in which women are already very prevalent (psychology, life science, social science) than in the math-intensive fields in which they are underrepresented but in which the number of females holding assistant professorships is at least commensurate with (if not greater than) that of males. That is, invitations to interview for tenure-track positions in math-intensive fields—as well as actual employment offers—reveal that female PhD applicants fare at least as well as their male counterparts in math-intensive fields. Along these same lines, our analyses reveal that manuscript reviewing and grant funding are gender neutral: Male and female authors and principal investigators are equally likely to have their manuscripts accepted by journal editors and their grants funded, with only very occasional exceptions. There are no compelling sex differences in hours worked or average citations per publication, but there is an overall male advantage in productivity. We attempt to reconcile these results amid the disparate claims made regarding their causes, examining sex differences in citations, hours worked, and interests. We conclude by suggesting that although in the past, gender discrimination was an important cause of women’s underrepresentation in scientific academic careers, this claim has continued to be invoked after it has ceased being a valid cause of women’s underrepresentation in math-intensive fields. Consequently, current barriers to women’s full participation in mathematically intensive academic science fields are rooted in pre-college factors and the subsequent likelihood of majoring in these fields, and future research should focus on these barriers rather than misdirecting attention toward historical barriers that no longer account for women’s underrepresentation in academic science.

Group Intelligence: Why Some Groups Are Better than Others.

Abstract We investigated how subjects performed alone and in groups on two written problems. We evaluated the relationship between cognitive and social-cognitive characteristics of group members—estimated both through written tests and videotape ratings—and group performance. We found that group products were of significantly higher quality than individual products. We also found that both cognitive and social-cognitive characteristics were related to group performance, and that videotape-derived estimates of these characteristics predicted group performance about as well as written measures. We present a method for conceptualizing and modeling group performance, and describe why we believe an integrative, multi-variable approach permits a richer understanding of group interaction.

Identifying and Assessing Tacit Knowledge: Understanding the Practical Intelligence of Military Leaders

Abstract Tacit knowledge (TK) is knowledge drawn from everyday experience that helps individuals to solve real-world, practical problems. This study applied a method for identifying and assessing TK to the domain of military leadership in order to understand why some leaders are more successful than others. Interviews were conducted with Army officers at three levels of leadership in order to identify the type of practical, experience-based knowledge that is not necessarily part of formal training or doctrine. Subsequently, the Tacit Knowledge for Military Leaders (TKML) inventory, consisting of a series of leadership scenarios, was developed to assess the amount of knowledge leaders possess. Three versions of the TKML were administered to a total of 562 leaders at the platoon, company, and battalion levels. At all three levels, TKML scores correlated with ratings of leadership effectiveness from either peers or superiors, and the scores explained variance in leadership effectiveness beyond a test of general verbal ability and a test of TK for managers. These results indicate that domain-specific TK can explain individual differences in leadership effectiveness and suggest that leadership development initiatives should include efforts to facilitate the acquisition of TK.

Sex Differences in Math-Intensive Fields

Despite impressive employment gains in many fields of science, women remain underrepresented in fields requiring intensive use of mathematics. Here we discuss three potential explanations for women’s underrepresentation: (a) male–female mathematical and spatial ability gaps, (b) sex discrimination, and (c) sex differences in career preferences and lifestyle choices. Synthesizing findings from psychology, endocrinology, sociology, economics, and education leads to the conclusion that, among a combination of interrelated factors, preferences and choices—both freely made and constrained—are the most significant cause of women’s underrepresentation.

When Scientists Choose Motherhood: A single factor goes a long way in explaining the dearth of women in math-intensive fields. How can we address it?

Jennifer was an extremely talented undergraduate, majoring in mathematics and engineering. Her grades and test scores were nearly perfect; her professors saw a bright future for her as an engineering professor and encouraged her to pursue a doctorate. In graduate school, she continued to excel, accumulating high-quality publications, fellowships and awards. She landed a premier postdoctoral position and was headed for a firsttier professorship. But she never applied for a tenure-track academic job. As a 33-year-old postdoc, she could not imagine waiting to have children until after tenure at age 40, nor could she imagine how she would juggle caring for a young family with the omnipresent demands of an assistant professorship. The harried lives of the two tenured mothers in her department convinced her that such a path was not for her. Jennifer made the choice to have a family and teach mathematics part-time at a local community college.

Intelligence, instruction, and assessment : theory into practice

Contents: Preface. R.J. Sternberg, Applying the Triarchic Theory of Human Intelligence in the Classroom. M. Krechevsky, S. Seidel, Minds at Work: Applying Multiple Intelligences in the Classroom. R.C. Schank, D.M. Joseph, Intelligent Schooling. H.L. Goodrich Andrade, D.N. Perkins, Learnable Intelligence and Intelligent Learning. J. Parziale, K.W. Fischer, The Practical Use of Skill Theory in Classrooms. A.R. Jensen, The g Factor and the Design of Education. J. Baron, Intelligent Thinking and the Reflective Essay. A. Demetriou, N. Valanides, A Three-Level Theory of the Developing Mind: Basic Principles and Implications for Instruction and Assessment. E.L. Grigorenko, Mastering Tools of the Mind in School (Trying Out Vygotskys Ideas in Classrooms).

Representational constraints on the development of memory and metamemory: a developmental-representational theory.

Traditional accounts of memory development suggest that maturation of prefrontal cortex (PFC) enables efficient metamemory, which enhances memory. An alternative theory is described, in which changes in early memory and metamemory are mediated by representational changes, independent of PFC maturation. In a pilot study and Experiment 1, younger children failed to recognize previously presented pictures, yet the children could identify the context in which they occurred, suggesting these failures resulted from inefficient metamemory. Older children seldom exhibited such failure. Experiment 2 established that this was not due to retrieval-time recoding. Experiment 3 suggested that young childrens representation of a pictures attributes explained their metamemory failure. Experiment 4 demonstrated that metamemory is age-invariant when representational quality is controlled: When stimuli were equivalently represented, age differences in memory and metamemory declined. These findings do not support the traditional view that as children develop, neural maturation permits more efficient monitoring, which leads to improved memory. These findings support a theory based on developmental-representational synthesis, in which constraints on metamemory are independent of neurological development; representational features drive early memory to a greater extent than previously acknowledged, suggesting that neural maturation has been overimputed as a source of early metamemory and memory failure.