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Pregnant employees experience considerable interpersonal discrimination. This study explores the range of possible reactions of observers to pregnancy self-disclosure, interpersonal discrimination and various allyship interventions, and the attentional processes that lead to those reactions. Consequently, it uncovers socio-cognitive processes underlying support for and backlash toward pregnancy in the workplace.

This study used a thought-listing technique to explore observers’ spontaneous thoughts related to pregnancy. Working adults were randomly assigned to read through one of the six scenarios depicting pregnancy self-disclosure, interpersonal discrimination and male allyship interventions (i.e. stating the organization’s anti-discrimination policy, confronting the transgressor by calling out sexism, pivoting the conversation to highlight the strengths of the pregnant employee and a hybrid intervention combining highlighting strengths and confrontation) after which participants listed the top three thoughts that came to their mind (1,668 responses). Responses were thematically analyzed to explore spontaneous reactions toward the pregnant employee, transgressor and ally in the scenario.

Surprisingly, across all scenarios, the most sexist thoughts emerged during pregnancy self-disclosure, even in the absence of any transgression. After a transgression occurred, any allyship intervention was better than none in eliciting lesser sexist backlash against the pregnant employee. Stating the organization’s anti-discrimination policy was most beneficial for the pregnant employee in eliciting the least sexist backlash but at the cost of generating unfavorable impressions of the ally. Calling out the transgressor’s bias elicited the most sexist backlash toward the pregnant employee, yet it created favorable impressions of the ally. In contrast, highlighting the strengths of the pregnant employee created the most favorable impression of the ally while eliciting a few sexist thoughts about the pregnant employee. Overall, the hybrid intervention was the most effective at balancing the competing goals of generating support for the pregnant employee, creating favorable impressions of the ally, as well as holding the transgressor accountable.

This study demonstrates that the type of allyship intervention critically redirects the attentional focus of observers to certain aspects of a discrimination episode and relevant schemas which can generate support or backlash toward targets, transgressors and allies, thereby advancing or obstructing equity and inclusion in organizations.

Data storytelling courses position students as agents in creating stories interpreted from data about a social problem or social justice issue. The purpose of this study is to explore two research questions: What themes characterized students’ iterative development of data story topics? Looking back at six years of iterative feedback, what categories of data literacy pedagogy did instructors engage for these themes?.

This project examines six years of data storytelling final projects using thematic analysis and three years of instructor feedback. Ten themes in final projects align with patterns in feedback. Reflections on pedagogical approaches to students’ topic development suggest extending data literacy pedagogy categories – formal, personal and folk (Pangrazio and Sefton-Green, 2020).

Data storytelling can develop students’ abilities to move from being consumers to creators of data and interpretations. The specific topic of personal data exposure or risk has presented some challenges for data literacy instruction (Bowler et al., 2017). What “personal” means in terms of data should be defined more broadly. Extending the data literacy pedagogy categories of formal, personal and folk (Pangrazio and Sefton-Green, 2020) could more effectively center social justice in data literacy instruction.

Implications for practice include positioning students as producers of data interpretation, such as role-playing data analysis or decision-making scenarios.

Data storytelling has the potential to address current challenges in data literacy pedagogy and in teaching critical data literacy.

Course descriptions provide a template for future data literacy pedagogy involving data storytelling, and findings suggest implications for expanding definitions and applications of personal and folk data literacies.

This article aims to help educators provide a holistic view of the LGBTQ community by highlighting children’s books that include non-parental LGBTQ characters.

The author selected over 80 children’s books honored by the American Library Association’s Rainbow Book List. Twenty-two books were analyzed that contain examples of LGBTQ adults existing beyond the homonormative nuclear family, e.g. two same-sex parents raising children.

The author discusses various ways of living represented in these books, such as chosen families, extended families, romantic partnerships and singlehood.

With the increased number of high-quality LGBTQ-inclusive children’s books published in the past decade, this study provides the foundation for educators to select various texts that reveal diverse representations of LGBTQ individuals.