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Record W4405487203 · doi:10.33137/cjal-rcbu.v10.43088

The Economics of Identity

2024· article· en· W4405487203 on OpenAlex
Tina Tianyi Liu

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

VenueCanadian Journal of Academic Librarianship · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsMcGill University
Fundersnot available
KeywordsIndigenizationIndigenousEquity (law)SociologyIdentity (music)Public relationsThematic analysisRepresentation (politics)CurrencyDiversity (politics)Political sciencePublic administrationSocial scienceEconomicsLawQualitative research

Abstract

fetched live from OpenAlex

This paper examines and critiques top-down institutional EDI policies and plans from Canadian academic libraries. Using David James Hudson’s critique of how the diversity model overemphasizes representation over meaningful action, this paper explores how the EDI plans and policies at Canadian academic libraries facilitate the exchange of racial capital, thereby reducing racialized identities to currency. To explore pathways forward, I conducted a thematic analysis of EDI plans and policies from all Canadian academic libraries. This thematic analysis informs strategies for how people within Canadian academic institutions can move beyond the diversity model to recentre meaningful and effective equity work. The paper closes with a call towards embedded EDI practices informed by Indigenous concepts of decolonial indigenization and relationality.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.006
Open science0.0010.000
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 head0.055
GPT teacher head0.306
Teacher spread0.251 · 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