Reporting and Subjectivity Traps: A Brief Opinion Article on Consciousness as Belief
Bibliographic record
Abstract
This work examines what we consider to be the two main limitations in consciousness science: the reliance on subjective reporting and the assumption of a coherent self. We propose that consciousness may function more as a belief system than an empirically verifiable fact, shaped by the subjective nature of experience and constrained by how we report it. Lacking objective evidence beyond self-reports, even advanced machines might mimic conscious behaviour under specific conditions. Concepts like phenomenological zombies—beings physically identical to us but devoid of consciousness—highlight the challenge of distinguishing true conscious experience from mere behavioural mimicry. Experimental designs frequently conflate metacognition (beliefs about perception) with consciousness itself, as seen in Higher-Order Thought theories. These frameworks suggest that our sense of being conscious may stem from metacognitive processes, often resulting in cognitive biases. Studies on brain regions associated with metacognitive accuracy further blur the distinction between consciousness and belief. Additionally, phenomena like delusional misidentification syndromes challenge the assumption of a stable, coherent self that reliably perceives and reports reality. By interrogating these assumptions, we reconsider consciousness not as an inherent property, but as an adaptive construct shaped to enhance survival. This perspective calls for a reevaluation of the fundamental nature of consciousness and the correct approach to studying it.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.007 | 0.018 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".