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Not Just Women, Not Just Latinas: Studying Phenomena and Not Groups

In addition to studying disparate groups or specific practices, which we have done in this volume, we need to consider how STEM communities are created and maintained—and to what extent they are inclusive. Scholars may study social phenomena like the distribution of power or what makes STEM academic and professional communities possible. While we are interested in the numerical representation of gendered and racially minoritized groups within STEM, we are not just interested in understanding individual characteristics or experiences. It is helpful to have counter-narratives that remind us not to adopt a deficit approach when thinking about student attrition within STEM. Beyond that, we are interested in improving social institutions. While keeping students central in our work, we need to examine power dynamics within universities, academic departments, and research teams.

This volume addresses the underrepresentation of Latina women in STEM. Yet, if we want to understand the broader challenges impeding diversity, equity, and inclusion in STEM, then we need to also study men and other racial minority groups. It is too easy to interpret findings about Latinas as specific characteristics of a single group. In fact, this is good research training. Researchers should not carelessly generalize.

However, studies of multiple groups of students lead to similar findings as the chapters in this volume. For example, multiple authors in this volume highlight the importance of mentoring Latinas (Garcia et al., 2020; Gonzalez, Molina, & Turner, 2020), which mirrors earlier work that examines Black and Latino men (e.g., Strayhorn, Long, Kitchen, Williams, & Stenz, 2013). Therefore, one way to advance future research is to focus on developing a research agenda around mentoring in STEM that includes multiple student groups, rather than to have disparate studies for combinations of minoritized statuses. Studying phenomena and not individual groups may even help researchers advocate for solutions that are expected to benefit more than a single group. How does decision-making work when it comes to choosing research topics, use of lab equipment, and the order of authors on publications? How could it work? How will STEM communities function if we do, in fact, get the numerical diversity we seek?

Considering Equity in STEM as a Global Challenge

Comparative and international studies will lead to insights about how access to STEM is stratified by disciplines across multiple contexts. If disciplines are “academic tribes” with their own cultures (Becher, 1989), it may be fruitful to examine STEM communities across countries to better understand what is possible through STEM disciplines even when the national policy contexts create unique circumstances. For example, scholars in the United States may point to the adverse effects of the ACT and SAT standardized tests in preventing access to STEM. Yet, countries like England have similar equity challenges, even though they do not use American standardized tests (Ro, Fernandez, & Alcott, 2018).

Scholars often attribute the lack of equity in STEM to broader, national- level equity' challenges. Yet puzzles remain about which countries make the greatest progress in improving equity and inclusion in STEM. Stoet and Geary (2018, 2019) identify what they call a “gender-equality paradox” in STEM; they' conclude that the share of women who earn university degrees in STEM fields is lower than expected in countries with higher gender equality. Conversely', countries that have higher gender inequality tend to have more women who graduate from STEM programs. Other scholars challenge Stoet and Geary’s analysis, but even they find a correlation between womens attainment in STEM and gender inequality across

75 countries (Richardson et al., 2020). Scholars find a similar pattern with enrollment and completion of massive open online courses (MOOCs) in STEM fields; there are smaller gender gaps in countries with more gender inequality (Jiang, Schenke, Eccles, Xu, & Warschauer, 2018). Certainly, the answer to improving diversity in STEM is not to increase gender inequality. Still, the gender-equality paradox challenges us to consider whether advancing women’s rights or improving gender norms and social constructions will in and of itself promote greater participation in STEM.

International and comparative studies can help us test assumptions and conceptual or theoretical frameworks in varying contexts. To make theoretical advances, we must first identify the conditions within which a theory predicts outcomes and then stretch a theory to its limits to understand the contexts where it is no longer useful for understanding a problem (DiMag- gio, 1995; Sutton & Staw, 1995). Here is one example of how a comparative study supports interesting findings. Smith and Fernandez (2017) analyze data from Canada and the United States to examine how education helps immigrants gain skills and do well in the labor market. The cross-national study helps the authors identify common relationships between education and skills for immigrants while understanding that outcomes persist based on the conditions of each country’s immigration system and labor market.

On a practical level, different countries invest in different types of data collection—and different types of secondary datasets open alternate possibilities for studying research problems. Ro and colleagues (2018) leverage a longitudinal dataset from England to examine how human capital and social capital frameworks are useful to examine the pathway to studying STEM. The study of university students in England confirms that women have lower odds of studying STEM, and it reveals that women have lower odds of studying STEM at the most prestigious universities in England (Ro et al., 2018). Looking globally may help us act locally.

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