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Record W4376852342 · doi:10.1386/macp_00063_1

Cruelty and democracy: Understanding Lippmann’s gambit

2022· article· en· W4376852342 on OpenAlexaff
Eric Van Rythoven

Bibliographic record

VenueInternational Journal of Media and Cultural Politics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsCarleton University
Fundersnot available
KeywordsCrueltyDemocracyLawSociologyPolitical scienceEnvironmental ethicsCriminologyPoliticsPhilosophy

Abstract

fetched live from OpenAlex

A paradox haunts Lippmann’s critique of democracy running through his early work in Public Opinion up through The Public Philosophy . Liberal democracies, despite their claim to securing space for human dignity and freedom, can be sites of incredible cruelty. From the racial prejudices cutting through American politics, to the way Americans treated adversaries during war, democracy appeared to do little to vitiate the human propensity to inflict suffering upon others. This article examines Lippmann’s understanding of cruelty as a recurring feature of democracy and how he grappled with the question of how to curb the democratic public’s worst impulses. I argue that while Lippmann offers an expansive understanding of cruelty his analysis continually gravitates towards the role of cruelty in democracy and how the existence of mobs and demagogues represent democracy’s ever-latent potential for cruelty. Exploring his thinking further, I suggest there are at least two distinct views on the origins and dynamics of cruelty in his work – what I designate ‘callous’ and ‘joyful’ cruelty – influenced by James and Freud respectively. Finally, I contend that recognizing the gravity Lippmann assigns to the problem of cruelty is important because it can help us understand his puzzling turn to natural law in The Public Philosophy . Here I suggest Lippmann’s turn to natural law should be read as a radical pragmatist gambit in which the myth of natural law is mobilized to create a ‘tradition of civility’ aimed at curbing democratic cruelty. When we attend to this side of Lippmann we see a version of him that is less a conservative reactionary and more an anxious critic desperate to ward off the darker impulses of democracy.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.421

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 studies0.0010.000
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 head0.109
GPT teacher head0.367
Teacher spread0.258 · 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
Published2022
Admission routes1
Has abstractyes

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