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Reading the silence: Canadian library responses to racial injustice

2021· article· en· W3169478004 on OpenAlexaffvenueabout
Amber Matthews

Bibliographic record

VenueCanadian Journal of Information and Library Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsWestern University
Fundersnot available
KeywordsInjusticeAccountabilityRacismSociologySilenceScope (computer science)Reading (process)Principal (computer security)Political sciencePublic relationsMedia studiesGender studiesLaw

Abstract

fetched live from OpenAlex

This paper presents the findings of a research study on the formal response of the Canadian library community to the mass Black Lives Matter (BLM) social movement in the wake of George Floyd’s death and the resulting global protests over the summer of 2020. The study employed mixed-method content analysis and its principal goals were to (a) identify formal responses between May to August 2020; (b) analyze themes across how the Canadian library community views and situates itself within conversations of racial justice; and (c) identify the scale and scope of commitments made for future accountability and research. The results show that one third (34%) of the Canadian library community formally responded with an organizational statement and even less situated their organizations as contributors to systemic racism in Canadian society.

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)0.008
metaresearch head score (Gemma)0.039
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 score0.917
Threshold uncertainty score0.602

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0430.013
Scholarly communication0.0080.003
Open science0.0030.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.013
GPT teacher head0.258
Teacher spread0.245 · 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

Citations4
Published2021
Admission routes3
Has abstractyes

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