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Record W2900938292 · doi:10.7202/1070738ar

Indigenous Course Requirements: A Liberal-Democratic Justification

2020· article· en· W2900938292 on OpenAlexaffvenueabout
Nicolas Tanchuk, Marc I. Kruse, Kevin McDonough

Bibliographic record

VenuePhilosophical Inquiry in Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicFeminist Epistemology and Gender Studies
Canadian institutionsMcGill UniversityUniversity of Winnipeg
Fundersnot available
KeywordsIndigenousDemocracySociologyArgument (complex analysis)EliteLiberalismLawPoliticsLaw and economicsPolitical scienceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

In Canada, several universities have recently implemented course requirements in Indigenous studies as a condition of graduation, while others are considering following suit. Policies making Indigenous course requirements (hereafter ICRs) compulsory have caused considerable controversy. According to proponents, a main purpose of ICRs is to address historical wrongs and to foster a more complete understanding of the ongoing relationship between Indigenous and non-Indigenous citizens. According to critics, making such courses compulsory effectively imposes illiberal restrictions on university students and faculty by limiting the epistemic aim of free inquiry, while wrongly prioritizing concern for the welfare of one social group over others. In this essay, we propose a liberal-democratic justification for ICRs that addresses these two worries about the ideals that may underwrite these courses. We argue that ICRs can be justified in liberal democratic terms insofar as they foster knowledge of what John Rawls refers to as ‘the constitutional essentials’ and remediate civic forms of what Miranda Fricker refers to as ‘epistemic injustices’. Universities, we claim have highly plausible role responsibilities to promote the civic epistemic aims identified by Rawls and Fricker, which are especially weighty due to the power university degrees confer, as part of the formation of a “democratic elite”. We then defend this line of argument against objections on the basis of academic freedom, by arguing that universities have reasons, internal to the search for truth to champion the political aims we identify.

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 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)0.001
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: none
Teacher disagreement score0.673
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.167
GPT teacher head0.420
Teacher spread0.253 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations20
Published2020
Admission routes3
Has abstractyes

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