While surveying some of the most vibrant humanities scholarship today, the goal of the conference is to think critically about the contemporary practice of interdisciplinarity.
The program is divided into 5 different panels of interdisciplinary intersection:
While surveying some of the most vibrant humanities scholarship today, the goal of the conference is to think critically about the contemporary practice of interdisciplinarity.
The program is divided into 5 different panels of interdisciplinary intersection:
This workshop series is designed for Stanford graduate students interested in learning more about and developing their skills in community-engaged scholarship and community-based research. Invited speakers include leaders and practitioners across disciplinary fields. Sessions will be held over lunch. Please check the website for location confirmation: haas.stanford.edu.
Please RSVP here for an accurate headcount for food.
Thriving as a Community Engaged Scholar: A Professional Development Series for Graduate Students is a series designed for Stanford graduate students interested in exploring both academic (tenure-line) and alternative academic career paths with a focus on community-engaged research.
November Focus: Publishing, Presenting, and Finding Funding for Community-Engaged Research
In this session, Dr. Antero Garcia will provide guidance and answer questions about publishing and presenting research and finding funding as a community engaged scholar.
Data Demo by Claudia Engel at 2019 Gear Up for Social Science Data Extravaganza
The goal of reproducible research is to improve scholarship by documenting data, code, and methods so results can be replicated and be subjected to scrutiny. R supports reproducible research through the creation of documents that combine content and code. This session will provide an overview of how to generate these documents and review some of the relevant R packages.
Gear UP for Social Science Data Talk by Emi Lesure
Data Demo for Qualitative Data Research: NVivo, Taguette, Python
Do you have “unstructured data” (e.g., government documents, interview transcripts, site videos) that you want to analyze qualitatively? Are you unsure about which tools fit your needs (small or large dataset, solo or team project) and how to use them?
Measuring, analyzing, and reporting data about learners, learning systems and learning programs have all contributed to understanding and optimizing learning experiences.
Women in Data Science@Stanford Earth features outstanding work done by outstanding women with the aim to educate, inspire and provide network opportunities for students, faculty and researchers. The workshop covers a range of topics in fundamental science as well as application areas in Earth resources, hazards, climate and sustainability.
Please join the Stanford Libraries' Green Library & the Stanford Graduate School of Business (GSB) Library and the Lane Medical Library for the...
2019 Gear Up for Social Science Data Extravaganza:
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