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Record W4394961614 · doi:10.1017/epi.2024.16

Echo Chambers and Moral Progress

2024· article· en· W4394961614 on OpenAlex
Tyler Wark

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEpisteme · 2024
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEcho (communications protocol)Nuclear magnetic resonancePhilosophyPhysicsComputer scienceComputer security

Abstract

fetched live from OpenAlex

Abstract In this paper, I argue that echo chambers pose a problem for moral progress because of their threat to moral reasoning. I argue for two theses about the epistemology of moral progress: (1) the practical utility thesis : moral reasoning plays an important role in improving moral judgments, and (2) the conflictive social reasoning thesis : the kind of moral reasoning that is important for moral progress involves social reasoning with disputants. Without some conflict, human beings will naturally reason in a biased and otherwise poor manner. Thus, good reasoning must be social so that reasoners who disagree can keep each other in check. These two theses explain why echo chambers are a problem for moral progress. I argue that echo chambers isolate individuals from reasoning with those they disagree with. This is because echo chambers act as a mechanism for discrediting those outside the chamber. If this is true, then the members of an echo chamber will only reason with those who agree with them. The result is that echo chamber members won't reason according to the conflictive social reasoning thesis. Reasoning will only reinforce their existing echoed beliefs rather than improve them.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.398

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 studies0.0000.000
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 head0.115
GPT teacher head0.305
Teacher spread0.190 · 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