“I Am Who I Am”: On the Perceived Threats to Personal Identity from Deep Brain Stimulation
Bibliographic record
Abstract
This article explores the notion of the dislocated self following deep brain stimulation (DBS) and concludes that when personal identity is understood in dynamic, narrative, and relational terms, the claim that DBS is a threat to personal identity is deeply problematic. While DBS may result in profound changes in behaviour, mood and cognition (characteristics closely linked to personality), it is not helpful to characterize DBS as threatening to personal identity insofar as this claim is either false, misdirected or trivially true. The claim is false insofar as it misunderstands the dynamic nature of identity formation. The claim is misdirected at DBS insofar as the real threat to personal identity is the discriminatory attitudes of others towards persons with motor and other disabilities. The claim is trivially true insofar as any dramatic event or experience integrated into one's identity-constituting narrative could then potentially be described as threatening. From the perspective of relational personal identity, when DBS dramatically disrupts the narrative flow, this disruption is best examined through the lens of agency. For illustrative purposes, the focus is on DBS for the treatment of Parkinson's disease.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".