Causes of Behavioral Processes: An Interview with Mario A. Bunge
Bibliographic record
Abstract
Mario A. Bunge is one of the most prominent philosophers and humanists of our time. His vast record of publications has covered, among others, epistemology, ontology, ethics, philosophy of natural and social sciences, philosophy of technology, and philosophy of mind. A topic that intersects many of these areas and is recurrent in Bunge’s work is causality. His analyses of the causal principle, and the redefinition of determinism into near-determinism have been applied to different philosophical issues that range from the causal role of neuronal functioning to the laws of social phenomena. Bunge has criticized functionalism, cognitivism, computationalism, behaviourism, and idealism in their attempt to explain human and non-human behaviour. This article results from an extensive interview held with Dr. Bunge in which we discussed a variety of conceptual issues related to the notions of causality and explanation in psychology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".