University Library Report on the Ithaka S+R Study on Improving Library Resources and Services for Indigenous Studies Scholars: University of Saskatchewan Context
Bibliographic record
Abstract
The University of Saskatchewan (U of S) Library is one of twelve institutions across Turtle Island / North America participating in a project with the goal of understanding how academic libraries can best support the research needs of Indigenous faculty. The U of S report is based primarily on semi-structured interviews with eight Indigenous professors at the U of S, as conducted by three librarians. The participants represented diverse backgrounds culturally, in their fields of study, and in terms of their years of experience as faculty members in the academy. Indigenous and Western research methodologies were incorporated in the development of this project, including: a grounded theory component which helped shape the analysis of the interviews, the encouragement of conversation and storytelling, multiple opportunities for consent, and an effort to meet the standards of Ownership, Control, Access and Possession of research data as delineated by the First Nations Information Governance Centre. Findings include: a lack of use of subject headings by Indigenous Studies scholars; requests for more oral histories (and access to them), more governmental and non-governmental organization reports and more Métis content; better access to Indigenous-related archival materials; and a strong demand for Data and GIS Library services. Recommendations are also included.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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".