Understanding ‘caring’ through biopolitics: the case of nurses under the <scp>N</scp>azi regime
Bibliographic record
Abstract
These days, discussions of what might be the 'essence' or the 'core' of nursing and nursing practice sooner or later end in a discussion about the concept of care. Most of the 'newer' nursing theories use this concept as a theoretical core concept. Even though these theoretical approaches use the concept of care with very different philosophical foundations and theoretical consistency, they concur in defining care as the essence of nursing and thereby glorify goodness as the decisive characteristic of nursing. These theoretical approaches neglect the fact that nursing is above all a profession with a societal task and is characterized by an asymmetrical power relation between nurses and their patients. Based on the results of a research project that analysed the role nurses played in the killing of psychiatric patients in Germany during the Nazi regime, I demonstrate that an approach based on the concept of care is not able to explain how nurses were able to commit crimes of such atrocity. These crimes were bound to an emotional investment that sustained the production of 'life unworthy of living'. In the case of nurses under the Nazi regime, certainly a kind of sadism was at issue that can only be explained if we recognize that the social bond is characterized by a certain tension; 'goodness' that caring theories assign to the social bond always coexists with the capacity for destruction. Using the Foucauldian theoretical framework of biopower and biopolitics enables one to analyse violence and power as integral parts of nurses' practice. Seen from this perspective, the killing of patients was part of a biopolitical programme and not a relapse into barbarism. The concept of care obscures the political agenda of nursing and does not provide a critical and political framework to analysing nursing practice.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.039 | 0.081 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.010 | 0.013 |
| 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 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".