Dataset Information

Comparing race, gender, age, and career categories in recognizing and grouping tasks.

ABSTRACT: The purpose of our research was to compare how participants weighed age, gender, race, and career categories in recognizing and grouping tasks. In Study 1, we used a category recognition task to compare participants' speeds in recognizing information from different categories. The results showed that participants recognized the gender information most quickly, followed by career, race, and age information. In Study 2, a categorization task was used to compare participants' category preferences. The results showed that the career category had the greatest weight, and the gender category had the lowest weight. Two targets who had different career identities were more possible considered as belonging to different groups than two targets with different gender, race or age identities. Our results have implications in understanding the weight of different categories, with gender and career category are the most important category that affects perception and evaluation.

SUBMITTER: Song J

PROVIDER: S-EPMC7233271 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Comparing race, gender, age, and career categories in recognizing and grouping tasks.

Song Jingjing J Li Lin L

PeerJ 20200515

The purpose of our research was to compare how participants weighed age, gender, race, and career categories in recognizing and grouping tasks. In Study 1, we used a category recognition task to compare participants' speeds in recognizing information from different categories. The results showed that participants recognized the gender information most quickly, followed by career, race, and age information. In Study 2, a categorization task was used to compare participants' category preferences. ...[more]

PMID: 32461837

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Project description:Increasing biomedical workforce diversity remains a persistent challenge. Recent reports have shown that biomedical sciences (BMS) graduate students become less interested in faculty careers as training progresses; however, it is unclear whether or how the career preferences of women and underrepresented minority (URM) scientists change in manners distinct from their better-represented peers. We report results from a survey of 1500 recent American BMS Ph.D. graduates (including 276 URMs) that examined career preferences over the course of their graduate training experiences. On average, scientists from all social backgrounds showed significantly decreased interest in faculty careers at research universities, and significantly increased interest in non-research careers at Ph.D. completion relative to entry. However, group differences emerged in overall levels of interest (at Ph.D. entry and completion), and the magnitude of change in interest in these careers. Multiple logistic regression showed that when controlling for career pathway interest at Ph.D. entry, first-author publication rate, faculty support, research self-efficacy, and graduate training experiences, differences in career pathway interest between social identity groups persisted. All groups were less likely than men from well-represented (WR) racial/ethnic backgrounds to report high interest in faculty careers at research-intensive universities (URM men: OR 0.60, 95% CI: 0.36-0.98, p?=?0.04; WR women: OR: 0.64, 95% CI: 0.47-0.89, p?=?0.008; URM women: OR: 0.46, 95% CI: 0.30-0.71, p<0.001), and URM women were more likely than all other groups to report high interest in non-research careers (OR: 1.93, 95% CI: 1.28-2.90, p?=?0.002). The persistence of disparities in the career interests of Ph.D. recipients suggests that a supply-side (or "pipeline") framing of biomedical workforce diversity challenges may limit the effectiveness of efforts to attract and retain the best and most diverse workforce. We propose incorporation of an ecological perspective of career development when considering strategies to enhance the biomedical workforce and professoriate through diversity.

Project description:Using social-cognitive career theory, we identified the experiential sources of learning that contribute to research self-efficacy beliefs, outcome expectations, and science identity for culturally diverse undergraduate students in science, technology, engineering, and math (i.e., STEM) majors. We examined group differences by race/ethnicity and gender to investigate potential cultural variations in a model to explain students' research career intentions. Using a sample of 688 undergraduate students, we ran a series of path models testing the relationships between the experiential sources, research self-efficacy beliefs, outcome expectations, and science identity to research career intentions. Findings were largely consistent with our hypotheses in that research self-efficacy and outcome expectancies were directly and positively associated with research career intentions and the associations of the experiential sources to intentions were mediated via self-efficacy. Science identity contributed significant though modest variance to research career intentions indirectly via its positive association with outcome expectations. Science identity also partially mediated the efficacy-outcome expectancies path. The experiential sources of learning were associated in expected directions to research self-efficacy with 3 of the sources emerging as significantly correlated with science identity. An unexpected direct relationship from vicarious learning to intentions was observed. In testing for group differences by race/ethnicity and gender in subsamples of Black/African American and Latino/a students, we found that the hypothesized model incorporating science identity was supported, and most paths did not vary significantly across four Race/Ethnicity × Gender groups, except for 3 paths. Research and practice implications of the findings for supporting research career intentions of culturally diverse undergraduate students are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Dataset Information

Comparing race, gender, age, and career categories in recognizing and grouping tasks.

Publications

Comparing race, gender, age, and career categories in recognizing and grouping tasks.

Similar Datasets

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