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Record W2909420809 · doi:10.3138/jelis.59.4.2018-0013

Education for the Common Good: A Student Perspective on Including Social Justice in LIS Education

2018· article· en· W2909420809 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Education for Library and Information Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsWestern University
FundersInstitute for Humane Studies, George Mason UniversityAmerican Library Association
KeywordsAccreditationCurriculumSociologySocial justiceContext (archaeology)Perspective (graphical)PedagogyEconomic JusticeRelevance (law)Library scienceEngineering ethicsPolitical scienceSocial scienceEngineeringLawComputer science

Abstract

fetched live from OpenAlex

This paper was produced as a collaborative project by a Progressive Librarianship class at an ALA-accredited Masters of Library and Information Science (MLIS) program located in Canada. Recent research in LIS has identified a need for issues of social justice to be discussed more prominently in LIS education. From a uniquely student perspective, the authors suggest how MLIS programs can incorporate social justice as a key component in LIS education. Specifically, they encourage pedagogy that supports critical thinking on issues of social justice and provides scaffolding for progressive change for the common good within a library context. This includes where social justice should appear in the LIS curriculum, who should teach about social justice, what topics are currently of relevance, and suggestions on key strategies for progressive change that can be taught in LIS education.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.033
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 head0.044
GPT teacher head0.418
Teacher spread0.374 · 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