Digital Literacy as a Theory of Power:Critical Pedagogy in a Library Digital Scholarship Centre
Bibliographic record
Abstract
What is the role of informal learning organizations in fostering digital literacy in Canadian universities?By informal learning environments, we mean spaces like libraries, centres for teaching and learning, academic success centres, makerspaces, and other facilities that make up the function of a contemporary university and which contrast with formal classrooms which have the authority and responsibility to conform to a particular curriculum, assign grades, and confer degrees.In this paper, the authors reflect on several years of operating a non-departmental research and teaching facility by connecting the pedagogical activities undertaken by its academic staff to educational and political theories with a specific focus on technology.The Digital Scholarship Centre (DSC) is an academic center operating out of the University of Alberta Library, which opened its doors in August 2019.This facility joins the Statistics Canada Research Data Centre as a new academic centre of the University of Alberta Library (CRDCN; Ahmed 2019).However, its mission differs from other academic centres in that it seeks to develop research through non-curricular initiatives.Consequently, the people working in the Centre host scholarly events, deliver non-credit workshops, and consult with researchers at any level-such as graduate students, post-doctoral students, faculty, and visiting scholars-on how to integrate computational methods into their study.The center is composed of an Academic Director, Head of Services, Digital Scholarship Librarian, and three Public Services Assistants, with casual staff like graduate students joining the facility as budgets permit.The use of the term "digital scholarship" is gaining ground across North American post secondary institutions, but in our first year of operations, it became evident that it was not easily understood within the University of Alberta community.In addition to practices like textual and spatial analysis, digital storytelling, data visualization and simulation, and extended reality, our definition of digital scholarship also includes makerspace practices (Ratto; Willett; Resch et al.), such as media production, 3D printing, 3D scanning and modelling, and laser cutting.Because the DSC was established within an academic library, our definition and approach to digital literacy pedagogy work is informed by the work of the American Library Association (ALA).This definition sees digital literacy as an extension of the information literacy, in that they both require "skills in locating and using information and in critical thinking" (ALA).Further, the ALA states: Digital literacy involves knowing digital tools and using them in communicative, collaborative ways through social engagement.ALA's Digital Literacy Task Force defines digital literacy as "the ability to use information and communication technologies to find, evaluate, create, and communicate information, requiring both cognitive and technical skills."However, due to our digital humanities training and foundations in constructionist philosophy of education (Papert; Papert and Harel), our understanding of digital literacy as a concept departs from the ALA's focus on requiring both cognitive and technical skills toward an umbrella concept of digital literacy developed by Aviram and Eshet-Alkalai (2006).Their conceptualization incorporates socio-emotional facets and non-linear organization of digital information for use and creation in the 21st century.Thus, by combining the facets of IDEAH • Vol. 3, Iss.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.019 | 0.093 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".