Inching Forward in the Face of Hegemonic Factors: Examining Metadata Contradictions Across University Indigenous Collections
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Changes to terminology take time and heighten tensions in language description, in preference of naming conventions, and institutional practices. External forces like the mandates of the United Nations Declaration on Indigenous Peoples, and the Canadian Federation of Library Associations (CFLA) recommendations for the Truth and Reconciliation Calls to Action, influence the actions taken by organizations and move us forward. However, other structural and systemic forces can impede these efforts. At the University of Calgary, decisions about which vocabularies to use are further muddied by different practices across our units, and the methods available to make updates to our systems. Our Library Managment System (LMS) needs to wait for updates from the vocabulary authorities, while our digital collections does not, allowing them to make big changes faster. By examining the applicable vocabularies in Canada, we can surface the hegemonic forces at work, that exist internal and external to the institution. For instance, while standardization aids in discovery, it also drives a hegemonic use of language which does not describe Canadian content such as Indigenous names. In grappling with these forces, we confront and oppose them as we work through the process of updating subject headings and descriptive language for Indigenous content within our systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.007 |
| 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 it