A Field Guide to Grad School: Uncovering the Hidden Curriculum

Bassett, Becca Spindel

doi:10.17763/1943-5045-91.1.138

Cited by 3 publications

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this knowledge is not accessible for all. As Calarco (2020:2) indicates “hiddenness perpetuates inequalities in grad school and in academia” where grad students from more privileged backgrounds tend to gain more rewards in academia since they have friends or family members who have been to grad school and can guide and help them uncover hidden curriculum. Information thus plays a critical role in eliminating educational and professional inequalities by supporting doctoral students and early career researchers to access key resources (Moore & Singley, 2019; Sloan & McPhee, 2013; Willson et al, 2022).…”

Section: Related Workmentioning

confidence: 99%

Navigating Higher Education: Insights from First‐Generation Doctoral Students

Ekmekcioglu

2023

Proceedings of the Association for Information Science and Tech

View full text Add to dashboard Cite

Access to higher education is a form of capital that is not always equally distributed. First‐generation doctoral students (FGDSs) face unique challenges and barriers which can make it difficult for them to navigate academic and institutional structures and access key resources and support. We present preliminary findings from interviews with 8 FGDS participants who pursue doctoral degrees in the field of information science in Canada. Interviews focused on identifying FGDSs' information practices in their pursuit of higher education. An inductive thematic analysis revealed the diverse information needs and sources utilized by this understudied population. The results provide insights about affective dimensions of information seeking and the role of mentors as key information intermediaries in supporting more diverse, inclusive, and equitable space for FGDSs. The poster concludes with implications for practice to improve the interfaces between FGDSs and higher education institutions as well as the broader academic landscape.

show abstract

Section: Related Workmentioning

confidence: 99%

Navigating Higher Education: Insights from First‐Generation Doctoral Students

Ekmekcioglu

2023

Proceedings of the Association for Information Science and Tech

View full text Add to dashboard Cite

show abstract

“…Young scholars, especially first‐generation students, people who identify as women and/or LGBTQ+, and people of color, learn early that there is a “hidden curriculum” to navigating academia (see, e.g., Calarco, 2020; Margolis, 2001). The hidden curriculum can be understood as the “habitus” of academia, the rules and norms that are not formally taught or explicitly conveyed that nevertheless constitute the cultural capital that enables success (Bourdieu, 1977, 1987).…”

Section: Learning the Hidden Curriculum From Laurie (Kt Albiston)mentioning

confidence: 99%

Learning from Laurie Edelman

Albiston,

Obasogie,

Morrill

2023

Law Soc Rev

View full text Add to dashboard Cite

Faculty members, students, policymakers, practitioners, and laypersons will learn from Laurie Edelman's brilliant scholarship for generations to come. She developed not only a new theory and a conceptual vocabulary for understanding the interplay of law and organizations-think, "legal endogeneity," "managerialization of law," or "symbolic structures" (Edelman, 2016)-but also a more precise account of the mutual influence between law and society. In this essay, we hold her scholarly contributions aside for a moment to explore what the three of us learned from Laurie in two of her most cherished professional roles as mentor and research collaborator. In many ways, she seemed happiest in these roles, whether advising students and early-career faculty (especially those most likely to be marginalized in academic circles, such as persons identifying as women and/or LGBTQ+, persons of color, persons with disabilities, or firstgeneration scholars) or working with scholars of diverse expertise and statuses on large, empirical projects.Catherine "KT" Albiston and Osagie Obasogie wrote the first two parts of this essay, respectively, "Learning the Hidden Curriculum from Laurie" and "Walking with Laurie," which explore what they learned from Laurie as a mentor. Laurie advised both as doctoral students at UC Berkeley: KT in the Jurisprudence and Social Policy (JSP) program and Osagie in the Department of Sociology. KT also collaborated with Laurie and multiple colleagues on the award-winning "Judicial Deference Project" (e.g., Edelman et al., 2011). Calvin "Cal" Morrill wrote the third part of this essay, "Learning Research Collaboration from Laurie." In this part of the essay, he explores what he learned from collaborating with Laurie on multiple, long-term empirical projects, especially the award-winning "School Rights Project" (e.g.,

show abstract

“…Computational social scientists currently work in academic departments, professional schools, nonprofit organizations (e.g., Code for America, Pew Research Center's Data Labs, and Urban Institute); tech companies (e.g., Meta, X, Google, Amazon, and Microsoft); international organizations (e.g., the World Bank and UN Global Pulse Labs); and government agencies (e.g., the US Federal Reserve, Census Bureau, and Office of Evaluation Sciences). Yet, how to become a computational social scientist still feels like a "hidden curriculum" (Barham and Wood 2022;Calarco 2020) to many social science PhD students. Because the field is so new, most social science PhD programs do not yet offer systematic training or dedicated advising to help students navigate careers as computational social scientists.…”

mentioning

confidence: 99%

Training Computational Social Science PhD Students for Academic and Non-Academic Careers

Kesari,

Kim,

Shah

et al. 2023

APSC

View full text Add to dashboard Cite

Social scientists with data science skills increasingly are assuming positions as computational social scientists in academic and non-academic organizations. However, because computational social science (CSS) is still relatively new to the social sciences, it can feel like a hidden curriculum for many PhD students. To support social science PhD students, this article is an accessible guide to CSS training based on previous literature and our collective working experiences in academic, public-, and private-sector organizations. We contend that students should supplement their traditional social science training in research design and domain expertise with CSS training by focusing on three core areas: (1) learning data science skills, (2) building a portfolio that uses data science to answer social science questions, and (3) connecting with computational social scientists. We conclude with practical recommendations for departments and professional associations to better support PhD students.

show abstract

A Field Guide to Grad School: Uncovering the Hidden Curriculum

Cited by 3 publications

References 1 publication

Navigating Higher Education: Insights from First‐Generation Doctoral Students

Navigating Higher Education: Insights from First‐Generation Doctoral Students

Learning from Laurie Edelman

Training Computational Social Science PhD Students for Academic and Non-Academic Careers

Contact Info

Product

Resources

About