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Record W2941958758 · doi:10.47925/2016.389

Actions, Consequences, and Community Boundaries

2016· article· en· W2941958758 on OpenAlexaff
Ann Chinnery

Bibliographic record

VenuePhilosophy of education · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicPragmatism in Philosophy and Education
Canadian institutionsYork University
Fundersnot available
KeywordsFraternityCommitPrivilege (computing)SociologyAgency (philosophy)LawValue (mathematics)Political scienceSocial science

Abstract

fetched live from OpenAlex

In his engaging and provocative paper, John Covaleskie draws our attention to the question of how moral communities that value tolerance ought to respond when members of their own community commit an intolerable act.I am grateful for Covaleskie's emphasis on moral communities, instead of the more common focus on individual moral development, agency, virtues, or moral reasoning.In what follows, however, it will become clear that Covaleskie and I hold quite different views on the moral and educative worth of University of Oklahoma President David Boren's response to the Sigma Alpha Epsilon (SAE) fraternity members who had been filmed participating in racist chants. Actions And consequencesAs Covaleskie recounts, the day after the video became public, Boren issued a statement in which he condemned the SAE fraternity members: "I have a message for you," he said."You are disgraceful.You have violated all that we stand for.You should not have the privilege of calling yourselves 'Sooners.'Real Sooners are not racist.Real Sooners are not bigots," and so on. 2Boren swiftly expelled Levi Pettit and Parker Rice (the two members of the SAE fraternity who were easily identifiable on the video), disbanded the fraternity chapter, and ejected SAE members from their frat house.Covaleskie characterizes Boren's response as "public moral education," and argues that his actions were "not only justified, they were morally exemplary, and they provide us with an example of moral pedagogy." 3

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.091
GPT teacher head0.293
Teacher spread0.202 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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