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Record W3045184003 · doi:10.5210/spir.v2018i0.10506

HATRED OF/AND DEMOCRACY: THE POLITICAL CONTRADICTIONS OF REDDIT’S MODERATION STRUCTURE

2020· article· en· W3045184003 on OpenAlexaffabout
Trevor Garrison Smith

Bibliographic record

VenueAoIR Selected Papers of Internet Research · 2020
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsCarleton University
Fundersnot available
KeywordsModerationHatredDemocracyPoliticsAuthoritarianismArgument (complex analysis)SociologyEpistemologyPolitical sciencePolitical economyLaw and economicsMedia studiesSocial psychologyLawPsychologyPhilosophy

Abstract

fetched live from OpenAlex

This paper seeks to interpret Reddit moderation as a problem of political theory, rather than as a debate between the merits of human moderation and algorithmic moderation. Analyzing Reddit’s moderation structure shows that both the human moderation and the algorithmic moderation reinforce a form of anti-politics which leaves users feeling like they have no input and thus no interest in the well-being of the subreddits in which they participate. Online governance structures are largely top down and authoritarian in nature, despite often being couched in democratic rhetoric, reflecting what Jacques Rancière describes as a hatred of democracy. By looking at the example of how r/Canada came to be widely disparaged on Reddit as a bastion of hate, I make the argument that the key to rooting out online hate is not through more human moderation or by giving algorithms more control, but by creating a democratic culture of buy-in through which users are empowered with responsibility for the quality of content in a discussion space.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.290
Teacher spread0.260 · 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 designBench or experimental
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

Citations0
Published2020
Admission routes2
Has abstractyes

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