Deep Brain Stimulation and Neuropsychiatric Anthropology – The “Prosthetisability” of the Lifeworld
Bibliographic record
Abstract
Deep Brain Stimulation (DBS) represents a key area of neuromodulation that has gained wide adoption for the treatment of neurological and experimental testing for psychiatric disorders. It is associated with specific therapeutic effects based on the precision of an evolving mechanistic neuroscientific understanding. At the same time, there are obstacles to achieving symptom relief because of the incompleteness of such an understanding. These obstacles are at least in part based on the complexity of neuropsychiatric disorders and the incompleteness of DBS devices to represent prosthetics that modulate the breadth of pathological processes implicated in these disorders. Neuroprostheses, such as an implanted DBS system, can have vast effects on subjects in addition to the specific neuropsychiatric changes they are intended to produce. These effects largely represent blind spots in the current debate on neuromodulation. Anthropological accounts can illustrate the broad existential dimensions of patients' illness and responses to neural implants. In combination with current neuroscientific understanding, neuropsychiatric anthropology may illuminate the possibilities and limits of neurodevices as technical "world enablers".
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.046 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".