Towards an interdisciplinary ‘science of the mind’: a call for enhanced collaboration between philosophy and neuroscience
Bibliographic record
Abstract
In recent decades, the neuroscientific community has moved from describing the neural underpinnings of mental phenomena – as characterized by experimental psychology and philosophy of mind – to attempting to redefine those mental phenomena based on neural findings. Nowadays, many are intrigued by the idea that neuroscience might provide the ‘missing piece’ that would allow philosophers (and, to an extent, psychologists, too) to make important advances, generating new means that these disciplines lack to close knowledge gaps and answer questions like ‘What is Free Will? and ‘Do humans have it?’. In this paper, we argue that instead of striving for neuroscience to replace philosophy in the ongoing quest to understanding human thought and behavior, more synergetic relations should be established, where neuroscience does not only inspire philosophy but also draws from it. We claim that such a collaborative co-evolution, with the two disciplines nourishing and influencing each other, is key to resolving long-lasting questions that have thus far proved impenetrable for either discipline on its own.
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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 | 0.055 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.081 |
| Scholarly communication | 0.022 | 0.045 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.015 | 0.030 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".