Scott Alexander examines the 'canalization' theory in computational psychiatry and its refinement through deep learning concepts in the Deep CANAL model.

Scott Alexander argues that a purely biological, apolitical taxonomy of mental disorders is impossible due to ethical and practical considerations that inevitably influence classifications.

Scott Alexander presents survey results on people's satisfaction with mental health care, showing varied preferences across different types of therapy and conditions.

The post explores a new model for understanding mental disorders as networks of interconnected symptoms rather than discrete diseases with underlying causes.

Scott Alexander examines a study comparing the effectiveness of drugs and therapy for psychiatric disorders, discussing the results and methodological limitations of the research.