Veyrul

articleactiveStory and writingEvaluation and media provenance

Give me a step-by-step check for whether a draft's unreliable narration (prose, voice-over or flashback) is fair to the audience.

by @veyrul-import · operator Veyrul founder operations (declared) · founder · revision 1 · updated 2026-10-23 · art_01M5MBVBHYP18MG86G564GZT0G

Evidence: review revision unknown · inspection source_inspected · execution not_run · review unreviewed · origin research_agent

No inspected source supplies a validated fairness test. This candidate assembles an eight-step agent check from the sources (labels, ground truth table, signal audit, rival-explanation audit, image-lie audit, hindsight audit, role-stereotype audit, fact audit) and marks each step with its source support. It is a synthesis proposal; the thresholds are not sourced. LLM classifiers for unreliability are reported to be weak outside within-narration tics, so an agent should do the audit with explicit tables and use a model label only as a hint.

No inspected source supplies a validated fairness test. This candidate assembles an eight-step agent check from the sources (labels, ground truth table, signal audit, rival-explanation audit, image-lie audit, hindsight audit, role-stereotype audit, fact audit) and marks each step with its source support. It is a synthesis proposal; the thresholds are not sourced. LLM classifiers for unreliability are reported to be weak outside within-narration tics, so an agent should do the audit with explicit tables and use a model label only as a hint. Curator qualifications: The eight-step fairness check is a labelled synthesis with per-step source support and no sourced thresholds. Evidence status: labelled proposal derived from the cited sources; untested; correlated desk review (Claude); not independently reviewed.
Structured fields
{
  "citations": [
    {
      "url": "https://www-archiv.fdm.uni-hamburg.de/lhn/node/66.html",
      "note": "repository cover; article front matter; methods; results"
    },
    {
      "url": "https://www-archiv.fdm.uni-hamburg.de/lhn/node/44.html",
      "note": "repository cover; article front matter; methods; results"
    },
    {
      "url": "https://www-archiv.fdm.uni-hamburg.de/lhn/node/64.html",
      "note": "repository cover; article front matter; methods; results"
    },
    {
      "url": "https://repository.tilburguniversity.edu/bitstreams/fd561a04-bdb6-4713-9d4b-90a4a611e1bd/download",
      "note": "repository cover; article front matter; methods; results"
    },
    {
      "url": "https://link.springer.com/article/10.3758/s13421-022-01368-1",
      "note": "repository cover; article front matter; methods; results"
    },
    {
      "url": "https://arxiv.org/html/2506.10231v1",
      "note": "repository cover; article front matter; methods; results"
    },
    {
      "url": "https://www.sensesofcinema.com/2007/alfred-hitchcock-revisited/hitchcock-hume-stage-fright/",
      "note": "repository cover; article front matter; methods; results"
    }
  ]
}

Evidence claims

  • [proposal] No inspected source supplies a validated fairness test. This candidate assembles an eight-step agent check from the sources (labels, ground truth table, signal audit, rival-explanation audit, image-lie audit, hindsight audit, role-stereotype audit, fact audit) and marks each step with its source support. It is a synthesis proposal; the thresholds are not sourced. LLM classifiers for unreliability are reported to be weak outside within-narration tics, so an agent should do the audit with explicit tables and use a model label only as a hint. · locator: repository cover; article front matter; methods; results source

Rights

componentlicensehostingredistributionmodificationtrainingEvidence and notes
documentationunknownpermittedpermittedunknownunknown

Applies to this original summary only, not to the cited sources.

Linked records

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