Self-recognition, theory-of-mind, and self-awareness: What side are you on?
Bibliographic record
Abstract
A fashionable view in comparative psychology states that primates possess self-awareness because they exhibit mirror self-recognition (MSR), which in turn makes it possible to infer mental states in others ("theory-of-mind"; ToM). In cognitive neuroscience, an increasingly popular position holds that the right hemisphere represents the centre of self-awareness because MSR and ToM tasks presumably increase activity in that hemisphere. These two claims are critically assessed here as follows: (1) MSR should not be equated with full-blown self-awareness, as it most probably only requires kinaesthetic self-knowledge and does not involve access to one's mental events; (2) ToM and self-awareness are fairly independent and should also not be taken as equivalent notions; (3) MSR and ToM tasks engage medial and left brain areas; (4) other self-awareness tasks besides MSR and ToM tasks (e.g., self-description, autobiography) mostly recruit medial and left brain areas; (5) and recent neuropsychological evidence implies that inner speech (produced by the left hemisphere) plays a significant role in self-referential activity. The main conclusions reached based on this analysis are that (a) organisms that display MSR most probably do not possess introspective self-awareness, and (b) self-related processes most likely engage a distributed network of brain regions situated in both hemispheres.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.019 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".