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Record W2564476812 · doi:10.7202/1070556ar

Safety, Dignity, and the Quest for a Democratic Campus Culture

2020· article· en· W2564476812 on OpenAlexvenueno aff
Sigal Ben‐Porath

Bibliographic record

VenuePhilosophical Inquiry in Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic Freedom and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsDignityDemocracySociologyEnvironmental ethicsSocial scienceEpistemologyPolitical sciencePhilosophyLawPolitics

Abstract

fetched live from OpenAlex

In his excellent paper, Callan (2016) differentiates intellectual safety, which fosters smugness, indifference and lack of effort, from dignity safety, which is needed for participation, learning and engagement.He suggests that college classrooms that reject the first and espouse the second would be ones that focus on "cultivating open-mindedness in a context of disagreement and fostering the civility that would secure dignity safety for all" (p.75).This is an important goal, and Callan makes here a significant contribution to the current discussion-both scholarly and public-on free speech, academic freedom and dignity safety.In what follows, I (1) expand on the suggestion that dignity safety is a threshold condition, contextualizing its role in providing access and on its place in the continuum of safety requirements, (2) consider the overlaps between dignity safety and intellectual safety, and subsequently reject nobility as an appropriate basis for creating a democratic atmosphere, and (3) suggest a democratic alternative to nobility and (Callan's version of) civility for the advancement of a democratic campus culture.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.016
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.074
Scholarly communication0.0160.011
Open science0.0010.014
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0040.001

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 head0.064
GPT teacher head0.372
Teacher spread0.309 · 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 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

Citations5
Published2020
Admission routes1
Has abstractyes

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