An evaluation of current perspectives on consciousness and pain in fishes
Bibliographic record
Abstract
Abstract There is growing societal and scientific interest in the welfare status of fish used for commercial enterprise. As animal welfare is primarily concerned with the quality of life of a conscious, sentient organism, the question of whether fishes are even capable of consciousness must first be addressed in order to assess their welfare status. Recently, there has been a resurgence of research investigating the biological basis for human consciousness, and our current understanding of the cognitive mechanisms underlying fish behaviour has likewise improved significantly. Combined, these research perspectives create an opportunity to better comprehend the phylogeny of traits associated with consciousness, as well as the emergence of consciousness itself during vertebrate evolution. Despite the availability of this literature, contemporary reviews or published studies investigating the probability of conscious states occurring in fishes often do so without considering new perspectives or data. In this paper, we review and critique recent publications that report equivocal conclusions favouring the absence or presence of consciousness in various fishes. By introducing other data into these analyses, we demonstrate that there are alternative perspectives which support the existence of consciousness in fishes as a plausible concept. An accurate assessment of the mental capacity of fishes will require enhanced knowledge of their forebrain neuroanatomy, an understanding of how such structures mediate behavioural responses, and an analysis of that information within the context of contemporary theory related to the evolution of consciousness in higher vertebrates.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".