The Draw a Scientist Test: A Different Population and a Somewhat Different Story.
Why this work is in the frame
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Bibliographic record
Abstract
This study examined Draw-a-Scientist-Test (DAST) images solicited from 212 undergraduate students for presence of traditional gender stereotypes. Participants were 100 males and 112 females enrolled in psychology or computer science courses with a mean age of 21.02 years. A standard multiple regression generated a model that accounts for variability in sexes of drawings consistent with past findings. The focus of this research, however, was in comparing results of our sample (college students) with previous studies that have that have used DAST with much younger (e.g., elementary-aged) students. Results were strikingly similar, suggesting either that gender stereotypes are widely persistent even among college science majors, or that DAST may not be a particularly sensitive measure despite its wide use. ----- The a Scientist Test (DAST) was first utilized by Chambers (1983) to examine stereotypic views of scientists among school children. Chambers' initial study examined strength and presence of modern sanitized, and older mythic, stereotypic images of scientist in 4, 807 children's (ages 5 to 11 years) drawings that were collected from 1966 to 1977. Chambers assessed presence of lab coats, eyeglasses, facial hair, symbols of research, symbols of knowledge, technological aspects, and captions that were believed to represent a stereotypical view of scientists. Chambers reported that 49% of this sample consisted of girls, but participants produced only 28 drawings of female scientists (0.56%). All of these female scientists were drawn by female participants. Subsequently, Fort and Varney (1989) gathered 1, 654 drawings of scientists through a national contest for 2nd through 12th grade school students. Fort and Varney received 135 drawings of female scientists. They reported that, the 8% depicted by our respondents is close to reflecting reality, (p. 9) given their estimate that women then made up roughly 6% of scientific and engineering workforce at that time. A careful analysis of DAST images reported by Newton and Newton's (1992) survey of 1, 143 primary school children (ages 4-11) suggests children draw more females at a younger age, but by sixth school year, males were drawn by 83% of participants. Following up, Newton and Newton (1998) surveyed 1000 children from reception (the UK equivalent of preschool/kindergarten) to grade 6 and, ...concluded that there were few significant changes to primary pupils' conceptions of science and scientist... (p. 1148). Over time, number of female scientists drawn has slightly increased. This may be due to changes in social perceptions, or to refinements in measure. For example, Matthews (1994) had 132 children from years 7, 8, and 10 generate two different drawings, out of this total, 66% of images were male, while 34% were female. Likewise, Maoldomhnaigh and Mholain (1990) considered effects of test administration instructions, eventually changing DAST instructions to Draw a Man or Woman Scientist. Stated thusly, 367 children (299 females and 68 males) between ages of 11 and 16 years provided drawings. Although boys in this sample almost exclusively drew males, 49% of girls drew a female. Brosnan (1999) modified task by re-framing it as a, draw-a-computer-user-test. For Brosnan, whose sample consisted of 395 children ages 5 to 11 years, males performed similar to males who complete standard DAST. Interestingly, 70% of females drew a female computer user, while only 4% of males drew a female computer user. Variations of DAST have been utilized in U.S. and Canada (e.g., Parsons, 1997), Ireland (e.g., Maoldomhnaigh & Hunt, 1990), Finland (e.g., Raty, 1997), England (e.g., Brosnan, 1999), Korea (e.g., Song & Kim, 1999); and Taiwan (e.g., She, 1998) with similar results. A recurrent finding in DAST literature is that scientists are stereotyped as being male by girls and this may serve as a limiting factor in their self--efficacy toward becoming scientists. …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it