MACS Fellowships

MACS (Mobilize, Articulate, Connect, Sustain)

 MACS is a Mellon funded IDH project led under the direction of PI Tanya Clement  for mobilizing existing university resources, articulating and elevating the importance of information work in the humanities, and connecting with community partners to develop a sustainable workforce development infrastructure in responsible information work.

Now accepting applications for Spring 2025. Deadline: November 29, 2024.

Responsible information work

With the increased use of data and AI in 2019, OCLC commissioned a report from the leaders of the Mellon-funded Collections as Data project to help chart library engagement with data science, machine learning, and artificial intelligence. The report, Responsible Operations: Data Science, Machine Learning, and AI in Libraries (2019), characterizes the challenges of doing data work in libraries and archives “responsibly” as “fostering organizational capacities for critical engagement, managing bias, and mitigating potential harm.”[i] In particular, workforce development based on core competencies and experiences of information work in libraries and archives that include digitization, information organization, management, access, and presentation is essential for decreasing gaps that persist within cultural heritage institutions where conceptualizing and operationalizing data workflows, policies, collections, and infrastructure must be balanced and sustainable. At the University of Texas at Austin, where community relationships at the libraries and archives are central to the work we do, we have found that developing a workforce that is responsible, experienced, and non-extractive requires meeting potentially conflicting requirements introduced by community needs, student training and professionalization specifications, and institutional capacity to support these goals.

Goals

MACS is a pilot project that (1) coordinates existing training programs for humanities students in information work in archives and collections with a career placement program that matches students with community partners with information work challenges; (2) evaluates and improves partnership outcomes for students, community partners, and educators; (3) articulates the value of humanities information work in terms of job opportunities in and outside of academia; and (5) explores sustainability plans for supporting similar programs beyond short-term funding. Funding will support project management; student fellowships; advisory board honoraria; and evaluation and reporting work. Deliverables will include detailed evaluations, conference presentations, a sustainability plan, and a case study report written for a public audience that identifies replicable approaches with lessons learned for community partners, university educators in the humanities and information sciences, and administrators. MACS seeks to increase the number of nonprofit organizations, workforce development programs, and humanities students that serve their communities by performing responsible information work.

Partners

The MACS model is in large part based on the work of Dr. Albert Palacios, the Digital Scholarship Coordinator in LLILAS Benson Latin American Studies and Collections and Adjunct Assistant Professor in the School of Information. MACS will demonstrate the value of responsible information work and help meet the needs of community partners by extending the LLILAS Benson program through CONNECT. Led by coordinator Alyssa Studer, UT’s CONNECT program works within UT’s Texas Career Engagement office to match advanced degree students to organizations with time and human capital constraints who need flexible and affordable solutions to address their data needs and challenges within short-term projects.

 

 

 

 

 

 

[i] Padilla, Thomas. “Responsible Operations: Data Science, Machine Learning, and AI in Libraries.” OCLC, 8 Dec. 2019, https://www.oclc.org/research/publications/2019/oclcresearch-responsible-operations-data-science-machine-learning-ai.html, page 6.