{
  "abstract": "The hard problem asks why physical processes are accompanied by experience. This paper develops a calibration audit for a prior evidential question: whether observations identify a psychophysical correspondence. Reference-relative hypotheses are separated from conventional relabellings. Finite reconstruction results characterize bridge ambiguity, and joint channel transformations show why accurate report prediction can leave it unresolved. Many-to-one bridges are treated through exact and approximate aggregation. Confidence sets propagate sampling error, dependence within independent blocks, episode selection, and noisy physical-state recognition. An exact synthetic benchmark separates approximately 90 percent report accuracy from bridge identification. A comparative benchmark adds weak predictive separation, correlated reports, selection, and channel misspecification across 12000 further replicates. In its weak combined-failure setting at the largest sample size, a plug-in likelihood comparison selects the wrong bridge in all 500 replicates; a correctly bounded audit retains both candidates. That protection has a cost: conservative bounds also leave some valid weak-signal cases unresolved. All procedures can select the wrong bridge under systematically inverted reference labels. The audit is an application of established identification and robust-inference principles, with usefulness demonstrated conditionally in synthetic models. A proposed motion protocol distinguishes reference consistency, operational accuracy, and intrinsic phenomenal identity. No human validation is claimed. Calibration can constrain psychophysical laws; it cannot choose between observationally equivalent metaphysical interpretations or explain why experience exists.",
  "abstract_shown": true,
  "affiliations": [
    "University of West London"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Kwan Hong TAN",
      "orcid": "0009-0003-9276-2829"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7rg7f7xsp9ga0.bib",
  "cited_by": 0,
  "doi": "10.5281/zenodo.23524881",
  "fulltext_url": null,
  "id": "7rg7f7xsp9ga0",
  "issns": [],
  "landing_url": "https://zenodo.org/records/23524881",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [],
  "openalex": null,
  "pdf_url": "https://zenodo.org/api/records/23524881/files/The%20Calibration%20Barrier%20in%20Consciousness%20Science%20-%20A%20Formal%20Research%20Strategy%20for%20the%20Hard%20Problem.pdf/content",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-21",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7rg7f7xsp9ga0.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:20:50Z",
      "native_id": "23524881",
      "source": "zenodo",
      "url": "https://zenodo.org/records/23524881"
    }
  ],
  "subjects": [],
  "title": "The Calibration Barrier in Consciousness Science: A Formal Research Strategy for the Hard Problem",
  "title_text": "The Calibration Barrier in Consciousness Science: A Formal Research Strategy for the Hard Problem",
  "type": "preprint",
  "updated_at": "2026-11-04T12:20:50Z",
  "url": "https://research.draconitic.com/paper/7rg7f7xsp9ga0",
  "venue": "Zenodo",
  "versions": []
}