Book Review: General Psychiatry: The Self in Neuroscience and Psychiatry
Bibliographic record
Abstract
The nature of the self has been an active topic of inquiry and debate since ancient times.Reflecting the complex questions arising from investigations into this area, The Self in Neuroscience and Psychiatry integrates contributions from specialists in the social sciences, psychology, neuroscience, philosophy, and psychiatry.Editors Tilo Kircher and Anthony David take a unique angle by focusing on self-representation in schizophrenia, a condition that has a disturbed sense of self at its core.The book is a compilation of 22 essays divided into 3 sections: "Conceptual Background," "Cognitive and Neurosciences," and "Disturbances of the Self: The Case of Schizophrenia."This final section is subdivided into an additional 3 areas: "Phenomenology," "Social Psychology," and "Clinical Neuroscience."While there is unavoidable overlap and repetition between some papers, the essays have distinct perspectives and address specific questions; therefore, any reiteration tends to improve cohesiveness rather than act as a detractor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.041 | 0.032 |
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".