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Record W3209146972 · doi:10.5206/elip.v4i1.13439

Shortcomings of Bibliographic Description in Service of Indigenous Peoples in Canada

2021· article· en· W3209146972 on OpenAlex
Amelia Hunter

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEmerging Library & Information Perspectives · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsWestern University
Fundersnot available
KeywordsIndigenousMetadataService (business)Library scienceWorld Wide WebPolitical scienceComputer scienceBusiness

Abstract

fetched live from OpenAlex

The marginalization of Indigenous Peoples in library catalogues and cataloguing standards is well documented. This article looks beyond Library of Congress Classification to analyze how the marginalization of Indigenous Peoples manifests in Machine Readable Cataloguing (MARC) and online public access catalogs (OPACs) to the detriment of Indigenous users. The rules that govern bibliographic description either obscure the presence of materials in a collection that represent Indigenous worldviews, or do not have the capacity to accurately record demographic terms related to Indigenous Peoples. This leads to inaccurate access points and culturally inappropriate metadata. Examples of projects and institutions innovating in this domain are examined. The harms cataloguers enact through adherence to bibliographic standards deserve critical and ethical analysis. These analyses and innovative projects are first steps towards better serving Indigenous users and reconciliation in libraries in Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.011
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.239
Teacher spread0.226 · 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