Rethinking Representation: Indigenous Peoples and Contexts at the University of Alberta Libraries
Bibliographic record
Abstract
Appropriate subject access and descriptive practices within library and information science are social justice issues. Standards that are well established and commonly used in academic libraries in Canada and elsewhere, including Library of Congress Subject Headings (LCSH) and Library of Congress Classification (LCC), continue to perpetuate colonial biases toward Indigenous peoples. In the fall of 2016, the University of Alberta Libraries (UAL) established a Decolonizing Description Working Group (DDWG) to investigate, define, and propose a plan of action for how descriptive metadata practices could more accurately, appropriately, and respectfully represent Indigenous peoples and contexts. The DDWG is currently beginning the implementation of recommendations approved by UAL’s strategic leadership team. In this paper we describe the genesis of the DDWG within the broader context of the libraries’ and the university’s responses to the Truth and Reconciliation Commission of Canada’s Calls to Action; outline the group’s activities and recommendations; and describe initial steps toward the implementation of those recommendations, with a focus on engaging local Indigenous communities. We reflect on the potential impact of revised descriptive practices in removing many of the barriers that Indigenous communities and individuals face in finding and accessing library materials relevant to their cultures and histories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.014 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".