Confronting Language, Representation, and Belief: A Limited Defense of Mental Continuity
Bibliographic record
Abstract
Abstract According to the mental continuity claim (MCC), human mental faculties are physical and beneficial to human survival, so they must have evolved gradually from ancestral forms and we should expect to see their precursors across species. Materialism of mind coupled with Darwin's evolutionary theory leads directly to such claims and even today arguments for animal mental properties are often presented with the MCC as a premise. However, the MCC has been often challenged among contemporary scholars. It is usually argued that only humans use language and that language as such has no precursors in the animal kingdom. Moreover, language is quite often understood as a necessary tool for having representations and forming beliefs. As a consequence, by lacking language animals could not have developed representational systems or beliefs. In response to these worries, we aim to mount a limited defense of the MCC as an empirical hypothesis. First, we will provide a short historical overview of the origins of the MCC and examine some of the motives behind traditional arguments for and against it. Second, we will focus on one particular question, namely, whether language as such is necessary for having beliefs. Our goal is to show that there is little reason to think language is necessary for belief. In doing so, we will challenge a view of belief that is widely accepted by those working in animal cognition, namely, representational belief, and we will argue that if belief is nonrepresentational, then different research questions and methods are required. We will conclude with an argument that to study the evolution of belief across species, it is essential to begin the study of subjects in their social and ecological environment rather than in contexts that are not ecologically valid along the social and ecological dimensions. Thus, rather than serving as a premise in an argument in favor of animal minds, the MCC can only be defended by empirical investigation, but importantly, empirical investigation of the right sort.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.039 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".