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Paradigms of Sex Research and Women in STEM.

ABSTRACT: Scientists' identities and social locations influence their work, but the content of scientific work can also influence scientists. Theory from feminist science studies, autoethnographic accounts, interviews, and experiments indicate that the substance of scientific research can have profound effects on how scientists are treated by colleagues and their sense of belonging in science. I bring together this disparate literature under the framework of professional cultures and show population-level trends supporting it. Drawing on the Survey of Earned Doctorates and the Web of Science, I use computational social science tools to argue that the way scientists write about sex in their research influences the future gender ratio of PhDs awarded across 53 subfields of the life sciences over a span of 47 years. Specifically, I show that a critical paradigm of "feminist biology" that seeks to de-essentialize sex and gender corresponds to increases in women's graduation rates, while "sex difference" research-sometimes called "neurosexism" because of its emphasis on essential, categorical differences-has negative effects on women's graduation rates in most fields.

SUBMITTER: Lockhart JW

PROVIDER: S-EPMC9365066 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Paradigms of Sex Research and Women in STEM.

Lockhart Jeffrey W JW

Gender & society : official publication of Sociologists for Women in Society 20210319 3

Scientists' identities and social locations influence their work, but the content of scientific work can also influence scientists. Theory from feminist science studies, autoethnographic accounts, interviews, and experiments indicate that the substance of scientific research can have profound effects on how scientists are treated by colleagues and their sense of belonging in science. I bring together this disparate literature under the framework of professional cultures and show population-level ...[more]

PMID: 35958390

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Project description:Imaging genetics studies involving participants with major depressive disorder (MDD) have expanded. Nevertheless, findings have been inconsistent. Thus, we conducted a systematic review and meta-analysis of imaging genetics studies that enrolled MDD participants across major databases through June 30th, 2017. Sixty-five studies met eligibility criteria (N = 4034 MDD participants and 3293 controls), and there was substantial between-study variability in the methodological quality of included studies. However, few replicated findings emerged from this literature with only 22 studies providing data for meta-analyses (882 participants with MDD and 616 controls). Total hippocampal volumes did not significantly vary in MDD participants or controls carrying either the BDNF Val66Met 'Met' (386 participants with MDD and 376 controls) or the 5-HTTLPR short 'S' (310 participants with MDD and 230 controls) risk alleles compared to non-carriers. Heterogeneity across studies was explored through meta-regression and subgroup analyses. Gender distribution, the use of medications, segmentation methods used to measure the hippocampus, and age emerged as potential sources of heterogeneity across studies that assessed the association of 5-HTTLPR short 'S' alleles and hippocampal volumes. Our data also suggest that the methodological quality of included studies, publication year, and the inclusion of brain volume as a covariate contributed to the heterogeneity of studies that assessed the association of the BDNF Val66Met 'Met' risk allele and hippocampal volumes. In exploratory voxel-wise meta-analyses, MDD participants carrying the 5-HTTLPR short 'S' allele had white matter microstructural abnormalities predominantly in the corpus callosum, while carriers of the BDNF Val66Met 'Met' allele had larger gray matter volumes and hyperactivation of the right middle frontal gyrus compared to non-carriers. In conclusion, few replicated findings emerged from imaging genetics studies that included participants with MDD. Nevertheless, we explored and identified specific sources of heterogeneity across studies, which could provide insights to enhance the reproducibility of this emerging field.

Project description:ObjectivesTo (1) characterize study paradigms used to investigate motor learning (ML) poststroke and (2) summarize the effects of different ML principles in promoting skill acquisition and retention. Our secondary objective is to evaluate the clinical utility of ML principles on stroke rehabilitation.Data sourcesMedline, Excerpta Medica Database, Allied and Complementary Medicine, Cumulative Index to Nursing and Allied Health Literature, and Cochrane Central Register of Controlled Trials were searched from inception on October 24, 2018 and repeated on June 23, 2020. Scopus was searched on January 24, 2019 and July 22, 2020 to identify additional studies.Study selectionOur search included keywords and concepts to represent stroke and "motor learning. An iterative process was used to generate study selection criteria. Three authors independently completed title, abstract, and full-text screening.Data extractionThree reviewers independently completed data extraction.Data synthesisThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension guidelines for scoping reviews were used to guide our synthesis. Thirty-nine studies were included. Study designs were heterogeneous, including variability in tasks practiced, acquisition parameters, and retention intervals. ML principles investigated included practice complexity, feedback, motor imagery, mental practice, action observation, implicit and explicit information, aerobic exercise, and neurostimulation. An additional 2 patient-related factors that influence ML were included: stroke characteristics and sleep. Practice complexity, feedback, and mental practice/action observation most consistently promoted ML, while provision of explicit information and more severe strokes were detrimental to ML. Other factors (ie, sleep, practice structure, aerobic exercise, neurostimulation) had a less clear influence on learning.ConclusionsImproved consistency of reporting in ML studies is needed to improve study comparability and facilitate meta-analyses to better understand the influence of ML principles on learning poststroke. Knowledge of ML principles and patient-related factors that influence ML, with clinical judgment can guide neurologic rehabilitation delivery to improve patient motor outcomes.

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Paradigms of Sex Research and Women in STEM.

Publications

Paradigms of Sex Research and Women in STEM.

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