PICTURE A SCIENTIST, Study notes of Rhetoric

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PICTURE A SCIENTIST:
A VISUAL RHETORIC APPROACH TO THE PROBLEM OF GENDER
DISPARITY IN STEM FIELDS
A dissertation submitted to the
Kent State University College of Arts and Sciences
in partial fulfillment of the requirements
for the degree of Doctor of Philosophy
By
Holly M. Wells
December 2012
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PICTURE A SCIENTIST:

A VISUAL RHETORIC APPROACH TO THE PROBLEM OF GENDER

DISPARITY IN STEM FIELDS

A dissertation submitted to the Kent State University College of Arts and Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy

By Holly M. Wells December 2012

ii

Dissertation written by B.A., Youngstown State University, 1984^ Holly M. Wells M.A., Youngstown State University, 2001 Ph.D., Kent State University, 2012

Approved by Chair, Doctoral Dissertation Committee Sara Newman, Professor of English Member, Doctoral Dissertation Committee Raymond A. Craig, Professor of English Member, Doctoral Dissertation Committee Derek Van Ittersum, Assistant Professor of English Member, Doctoral Dissertation Committee Laura G. Leff, Professor of Biology Member, Doctoral Dissertation Committee Mandy J. Munro-Stasiuk, Professor of Geography

Accepted by Chair, Department of English Robert W. Trogdon Dean, College of Arts and Sciences Raymond A. Craig

v

List of Figures

  • Chapter 1: Statement of Problem and Literature Review.............................................. Acknowledgments.................................................................................................. xi
    • Importance of the Problem......................................................................................
    • Purpose and Scope of the Study..............................................................................
    • Assumptions............................................................................................................
    • Textbooks and Children
    • Rhetoric of Science
    • Visual Rhetoric
  • Chapter 2: Methodology
    • Theoretical Foundation
    • Research Method
      • Data
      • Data Analysis Procedures
      • Triangulation of Methods
      • Limitations of Methodology
      • Ethical Issues
    • Conclusion
  • Chapter 3: Glencoe Life Science
    • Overview
    • Results
    • Discussion
    • Results
    • Discussion
    • Summary
  • Chapter 4: McDougal Littell
    • Overview
    • Results
    • Discussion
    • Results
    • Discussion
    • Summary iv
  • Chapter 5: Prentice Hall Life Science
    • Overview
    • Results
    • Discussion
    • Results
    • Discussion
    • Summary
  • Chapter 6: Conclusions and Future Research
    • Summary
    • Conclusions
    • Implications.........................................................................................................
    • Limitations
    • Recommendations for Future Research
  • BIBLIOGRAPHY
  • APPENDIX A
  • APPENDIX B............................................................................................................
  • APPENDIX C............................................................................................................
  • APPENDIX D
  • APPENDIX E
  • South Dakota Dry Lands. May 1936. Fig. 1. Arthur Rothstein. The bleached skull of a steer on the dry sun-baked earth of the
  • Fig. 2. The famous photograph of the flag raising at Iwo Jima
  • Fig. 3. Horizontal photo layout.
  • Fig. 4. Saturation. From Clark & Wiebe (2000), Scientific Visualization.
  • Fig. 5. Depth
  • Fig. 6. The Rothstein photo that caused controversy in the late 1930s.
  • Fig. 7. Photo Survey – Visual Rhetoric Analysis Part 1.
  • Fig. 8. Triangulation of research methods.
  • Fig. 9. The basic cat.
  • Fig. 10. Gender distribution among editorial staff.
  • Fig. 11. Doctoral degrees among editorial staff.
  • Fig. 12.
  • Fig. 13.
  • Fig. 14.
  • Fig. 15. Low color differentiation.
  • Fig. 16.
  • Fig. 17.
  • Fig. 18.
  • Fig. 19. Deep perspective...............................................................................................
  • Fig. 20.
  • Fig. 21.
  • Fig. 22.
  • Fig. 23.
  • Fig. 24.
  • Fig. 25. Examples of naturalistic depth and artificial depth.
  • Fig. 26. Percentages of images in naturalistic range in each of the Visual categories
  • Fig. 27.
  • Fig. 28. White man in lab coat giving a presentation.
  • Fig. 29. Early humans.
  • Fig. 30. Two scientists examine a rock of salt.
  • Fig. 31. Generic male.
  • Fig. 32. Eye doctor and patient.
  • Fig. 33. A boy gives a presentation to his fellow students. vi
  • Fig. 34. Boys use the Internet, as a girl stands by, watching.
  • Fig. 35. Father and infant son.
  • Fig. 36. Foundational work in cancer research done by prominent female scientists
  • Fig. 37. Comparing a printout with the image on an electron microscope.
  • Fig. 38.
  • Fig. 39. Kindergarten teacher.........................................................................................
  • Fig. 40. Teen party.
  • Fig.
  • Fig. 42.
  • Fig. 43.
  • Fig. 44.
  • Fig. 45. Teens having a party.
  • Fig. 46. Woman performs Heimlich maneuver on man.................................................
  • Fig. 47. Woman performs Heimlich maneuver on woman.
  • Fig. 48. Gender distribution among editorial staff.
  • Fig. 49. Doctoral degree holders among editorial staff.
  • Fig. 50.
  • Fig. 51.
  • Fig. 52.
  • Fig. 53.
  • Fig. 54. Lack of context
  • Fig. 55.
  • Fig. 56.
  • Fig. 57. Woman working at computer station................................................................
  • Fig. 58. Hyperreal perspective created by an extreme wide-angle lens.........................
  • Fig. 59.
  • Fig. 60. Abstraction of light and shade
  • Fig. 61. Low contrast
  • Fig. 62.
  • Fig. 63.
  • Fig. 64. A naturalistic photograph
  • Fig. 65.
  • Fig. 66. Oblique horizontal angle.
  • Fig. 67.
  • Fig. 68. High vertical angle............................................................................................
  • Fig. 69. "Save the Children" advertisement featuring high vertical angle vii
  • Fig. 70. High-vertical-angle image
  • Fig. 71. Percentages of images in naturalistic range in each of the Visuals categories
  • Fig. 72. Comparing McDougal Littell visuals results to Glencoe.
  • Fig. 73. Raw numbers represented as a chart.................................................................
  • Fig. 74. Generic male figure used to illustrate a bodily system.
  • Fig. 75. Young male in a nontraditional role for a child musician: as a flautist.
  • Fig. 76. Boy and girl sit on invisible surface; boy appears to levitate.
  • Fig. 79. Girl holds recycling while boy throws it into bin
  • Fig. 78. Girls doing pull-ups on the playground.
  • Fig. 77. A woman doctor treating a female patient........................................................
  • Fig. 80. Boy and girl demonstrate experiment.
  • Fig. 81. Marie Curie.
  • Fig. 82. Charles Darwin
  • Fig. 83. Sylvia Earle, chief scientist at the NOAA.
  • Fig. 84. Generic human, in this case a female.
  • Fig. 85. Gardening.
  • Fig. 86. Sylvia Earle.......................................................................................................
  • Fig. 87. Boy discussing experiment with girls.
  • Fig. 88. Children recycle items.
  • Fig. 89.
  • Fig. 90. Distribution of terminal degrees.
  • Fig. 91. Education levels of contributors
  • Fig. 92. Saturation.
  • Fig. 93. Modulation........................................................................................................
  • Fig. 94. Differentiation.
  • Fig. 95. Contextualization.
  • Fig. 96. Girl watches as boy performs experiment.
  • Fig. 97. Representation of detail.
  • Fig. 98. A girl performing an experiment using pens to represent traits.
  • Fig. 99. Depth.
  • Fig. 100. Somewhat shallow perspective.
  • Fig. 101. Illumination.
  • Fig. 102. Abstract light source.
  • Fig. 103. Brightness.
  • Fig. 104. Coding orientation.
  • Fig. 105. Girls watch as boy performs experiment. viii
  • Fig. 106. Horizontal angles.
  • Fig. 107. Marine biologist from frontal horizontal angle.
  • Fig. 108. Girl photographed from an oblique angle.......................................................
  • Fig. 109. Vertical angles.
  • Fig. 110. High vertical angle and wide-angle lens.........................................................
  • Fig. 111. Middle vertical angle.
  • Fig. 112. Low vertical angle.
  • Fig. 113. Percentages of photos in naturalistic range in each Visuals category.
  • Fig. 114. Comparing naturalistic range results in all three texts.
  • Fig. 115. People in the 2005 edition of the Prentice Hall text.
  • Fig. 116. Dr. Jonas Salk vaccinating a girl against polio.
  • Fig. 117. Journalist Marjory Stoneman Douglas
  • Fig. 118. Ariko Iso, a trainer with the Pittsburgh Steelers
  • Fig. 119. Young woman in the kitchen, chopping angiosperms.
  • Fig. 120. Female biologist depicted in a nontraditional job.
  • Fig. 121. Generic human = black, white, brown, Asian, male, female.
  • Fig. 122. Generic humans depicted as real youths.........................................................
  • Fig. 123. Forestry vs. health care professions.
  • Fig. 124. Girls watch boy taking notes.
  • Fig. 125. Boy and girl perform statistical experiment.
  • Fig. 126. Boy performs experiment as girl watches.
  • Fig. 127. The scientific method.
  • Fig. 128. Symptoms of heart attack.
  • Table 1. List of Tables
  • Table 2.
  • Table 3.
  • Table 4.
  • Table 5.
  • Table 6.
  • Table 7.
  • Table 8.
  • Table 9.
  • Table 10.
  • Table 11.
  • Table 12.
  • Table 13.
  • Table 14. Visual enthymeme for Fig. 43.
  • Table 15. Visual enthymeme for Fig. 44.
  • Table 16. Visual enthymeme for Fig. 45.
  • Table 17. Visual enthymeme for Figures 46–47.
  • Table 18.
  • Table 19.
  • Table 20.
  • Table 21.
  • Table 22.
  • Table 23.
  • Table 24.
  • Table 25.
  • Table 26.
  • Table 27.
  • Table 28.
  • Table 29.
  • Table 30.
  • Table 31.
  • Table 32.
  • Table 33.
  • Table 34.
  • Table 35. x
  • Table 36.
  • Table 37.
  • Table 38.
  • Table 39.
  • Table 40.
  • Table 41.
  • Table 42.
  • Table 43.
  • Table 44.
  • Table 45.
  • Table 46. Visual enthymeme from forestry professions.
  • Table 47. Visual enthymeme from health care professions.
  • Table 48. Visual enthymeme of the page layout............................................................
  • Table 49. Visual enthymeme from Fig. 123.
  • Table 50. Visual enthymeme from Fig. 125.
  • Table 51. Visual enthymeme from Fig. 126.
  • Table 52. Visual enthymeme from Fig. 127.
  • Table 53.
  • Table 54.

xi

ACKNOWLEDGMENTS

Among the many people whose support and wisdom I need to acknowledge and to whom I must express my gratitude are the following: First, to the best chair and mentor in the world, Sara Newman; if she gives every grad student the attention she has given me, she must not sleep. To my committee, comprising Ray Craig and Derek Van Ittersum, as well as Mandy Munro-Stasiuk and Laura Leff, for finding time in their busy schedules to give me constructive feedback and have scholarly discussions about this project. To the LRSP faculty and my fellow students at Kent; to Hugh McCracken, Terry Benton, Bege Bowers, and Rick Shale; to the Igniting Streams of Learning in Science program; to Dawn Lashua, whose patient support never wavered. To my sons, Julian Altomare, and Stefan Domonkos, and to my incredible husband and best friend, Jaryl Altomare, whose contributions to this project can scarcely be listed. Thank you.

Trust in the LORD with all thine heart; and lean not unto thine own understanding. In all thy ways acknowledge Him, and He shall direct thy paths. (Proverbs 3: 5–6)

Chapter 1: Statement of Problem and Literature Review

In December 2008, the National Science Foundation (NSF) updated statistics on race, gender, disability, and marital status of people in science, technology, engineering, and mathematics (STEM) careers, from business to academia (National Science Foundation, 2011).^1 While more women are entering the traditionally male STEM careers, the numbers are still well below those of men. The NSF considers this disparity a serious problem, offering grants to support research to help solve it (ADVANCE: Increasing the Participation and Advancement of Women in Academic Science and Engineering Careers [ADVANCE]). But without a firm understanding of where the problem begins, researchers are finding it difficult to make changes that will successfully bring more women into the STEM fields. According to the NSF, women are vastly underrepresented in STEM careers in both business and academia, with fewer than 35% of jobs in both areas; when they do work in academia, they are more likely to be postdocs or adjuncts, both of which are lower-paying and lower-prestige careers; and in almost every job category, they make

(^1) It is important here to clarify my use of STEM throughout this dissertation. At times, it may appear that I am using “STEM” and “science” interchangeably. However, I have several reasons for switching back and forth. In some cases, research I am citing examined only sciences, and in others, all of STEM. In the case of classroom research, engineering and technology courses are not common (especially in the middleschool years), so research usually comes from science and/or mathematics courses. I have attempted to be specific about the subject(s) being discussed in each instance.

significantly less money than men. However, many young girls may not know this: I asked 24 high school girls involved in a science education program entitled Igniting Streams of Learning in Science (ISLS) whether they thought women were underrepresented in STEM fields. Nearly half of those surveyed responded either that enough women were pursuing STEM careers, or that they were not sure. While this is hardly a scientific study, the results are interesting because the subjects had been in ISLS for ten months and were perhaps more aware of issues in the field than average high school juniors and seniors. The fact that 11 of 24 girls in a science program were not aware of the gender disparity issue should concern educators and employers all over the country.

Importance of the Problem Gender Stereotyping in STEM Fields: How Do We Know a Problem Exists?

A quick glance at the NSF statistics on gender and STEM fields is enough for most researchers to conclude a problem exists. While an exhaustive listing of all the ways in which self-identifying females fall short of males in STEM careers (e.g., in sheer numbers, salaries, levels of unemployment, etc.) would take too much time in this document, here are a few examples:  Women represent only about 34% of scientists and engineers in business and industry.  Women represent only 32% of STEM Ph.D. holders in academia.

intimidating and risky (Carlone, 2004). Thus, it is important that research focus on images to which girls in this age group are routinely exposed. A review of recent literature on gender in children’s books, including picture books and textbooks, exposes that, although some improvements have been made, inequalities still exist in both the number of women (vs. men) represented and the kinds of activities and occupations women (vs. men) engage in as illustrated in these books (see e.g., Turner-Bowker, 1996; Schau and Scott, 1984; Evans and Davies, 2000; Kelly, 1985; Sadker and Sadker, 1994; Elgar, 2004; Whiteley, 1996). Studies have also been conducted on the use of gendered language in textbooks (see e.g., Porreca, 1984; Harrison and Passero, 1975; Poulou, 1997; and Campbell and Schram, 1995). However, little research exists in the area of visual rhetorical analysis—that is, in closely examining graphics in science textbooks or electronic resources to determine what those graphics are arguing, and how. The few existing studies have not focused on gender as a variable (e.g., Dimopoulos, et al., 2003); similar studies that have focused on gender (Kelly, 1985; Bazler and Simonis, 1991) have simply counted the appearances of each gender and tracked the roles of the subjects. Thus far, research has not scrutinized the gendered relationships depicted in textbook photos and graphics. Why is the image important to a study of gender and career choices? On the surface, it may not seem likely that young people choose their careers based on pictures they have seen; however, we know now that the media do influence people’s perceptions of science and scientists (see e.g., Steinke et al., 2007; Steinke, 2005, 1997), as well as perceptions of gender and gender roles. For instance, a study of children’s science

television shows (Steinke and Long, 1996) demonstrated that men appear twice as often as women in scientist roles, and that women are much more likely to be assistants, apprentices, students, or science reporters than science experts. Steinke and Long (1996) argue that children in particular may be influenced by images they see in the media because they are still developing the ability to interpret the world around them, and because they are exposed to abundant mass media sources before starting school. Supported by a large body of evidence (including studies of children’s books, textbooks, and other media), it is easy to speculate about a connection between the images of scientists presented to kids, and the fact that kids overwhelmingly imagine scientists as White males. The numbers, unfortunately, seem to support this conclusion (nsf.gov). The specific purpose of this study is to add to the expanding theories of visual rhetoric by applying principles of visual analysis, based on the social semiotic theory proposed by Halliday (1978) and adapted by Kress and Van Leeuwen (Reading images: The grammar of visual design, 1996), to images from a collection of current life science textbooks for middle-school students. Additionally, the study aims to apply rhetorical analysis (based on enthymemes and repetition) to images to look for and interpret visual arguments. Because we know that the middle school years are important in girls’ changing attitudes about STEM careers, it is imperative that we begin to build a stronger body of evidence concerning why girls drop away from science at these ages, and to find ways to prevent this from happening. I acknowledge that science textbooks are hardly the only influences on young girls’ attitudes about their career choices at this, or any, age. Indeed, peers and parents

An important assumption of any study that has gender as one of its variables is that gender is a simple, biological binary. Studies in the past twenty years or so are beginning to break down this assumption. Influenced by such feminist works as Butler’s (1990) Gender Trouble , some researchers in humanities and social sciences have gradually begun to treat gender as a continuum, rather than as an either/or proposition. For the purposes of this study, it may not be necessary to settle upon an accepted set of gender categories. Although it is true that many individuals fall somewhere between “male” and “female” on the spectrum, just as the color grey can fall anywhere on the spectrum between white and black, it is probably also true that most of the people being researched and to whom this research will be the most useful identify at or fairly close to one or the other—i.e., male or female. Also important, young people going through puberty experience a process of socialization into gender roles during this development, and many of the artifacts of this process—from textbooks to television to clothing—promote a binary vision of gender. As such, it may not be particularly useful to consider gender on a continuum if in fact the majority of people affected by the results do not consider themselves to be on a gender “spectrum.” It may, however, be useful to consider that those who do fall somewhere in between “male” and “female” may, or may not, identify more often with one absolute gender than the other—and in these cases, results will be useful to those individuals as they identify in their approach to STEM careers. For those individuals who choose not to identify with a gender absolute, statistics regarding gender disparities in STEM careers may not be especially interesting

or meaningful, anyway. Furthermore, attempting to add a gender continuum as a variable may complicate the project unnecessarily, with results that say perhaps little different about the images’ effects on readers than keeping the study a simple consideration of male or female representation. As mentioned above, however, the presumption is that children are affected by what they read and view in their textbooks—by no means a presumption safe to make without evidence, which I detail in the following section.

Textbooks and Children In this section, I illustrate, through a series of recent examples, how the scholarship in science education lags somewhat behind feminist language studies in its operationalization of sex and gender in language studies. Then, I review the literature dealing with gender in science texts, noting a significant gap existing in research on gender and power roles in textbook photographs. Finally, I place the current study within that gap. An informative and thorough review by Brotman and Moore (2008), entitled “Girls and science: A review of four themes in the science education literature,” examines the entirety of peer-reviewed journal scholarship on science teaching (which comprises about eight journals). In their introductory paragraphs, the authors implicitly situate themselves as social constructionists by stating that they see gender as a continuum, not a binary, and as constructed in conjunction with other variables such as race and religious beliefs. (Biological sex, on the other hand, remains to be treated as more or less a given of birth.) The authors isolate four basic themes in gender research