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Record W7072229894

Walking Together: An Investigation of Indigenous Students’ Relationship to the Academic Library

2023· other· en· W7072229894 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2023
Typeother
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousAcademic libraryService (business)Ideal (ethics)Graduate studentsPerception
DOInot available

Abstract

fetched live from OpenAlex

Academic libraries have begun to acknowledge institutional gaps in knowledge and cultural understanding. To attend to Indigenous students’ emergent library and information needs, we interviewed Indigenous undergraduate and graduate students at the University of Toronto to investigate their relationships to the library system. We found that while students understood the need for strong library and research skills, the library lacked much of what Indigenous students needed to be successful in its collections, programming, and services. The Indigenous students revealed that the library was not a space of cultural safety, nor did it reconnect with the Lands and Waters that were necessary for successful research and relations. Instead, current library practices exposed Indigenous students to culturally damaging and traumatic materials and failed to protect them from profiling and racialization in physical spaces. We call for a transformation and decentering of traditional library practice toward a more just and equitable future praxis with Indigenous students.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score0.285

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0180.005
Scholarly communication0.0060.004
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.029
GPT teacher head0.244
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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