An analysis of <scp>E</scp>ngland's nursing policy on compassion and the 6<scp>C</scp>s: the hidden presence of M. <scp>S</scp>imone <scp>R</scp>oach's model of caring
Bibliographic record
Abstract
In 2012, chief nursing officers (CNO) in England published a policy on compassion in response to serious criticisms of patients' care. Because their objective is fundamentally to shape nursing, this study argues, following Popper, that the policy should be analysed. An appraisal tool, developed from Popper, Gadamer, Jauss and Thiselton, is the framework for this analysis. The CNO policy document identified six values and behaviours, termed '6Cs', required by all nurses, midwives and care staff. The document contains no data, references or acknowledgements, but is similar to the 6Cs defined by the Canadian nursing nun, Sister M. Simone Roach, in her theory of caring published 30 years earlier. Roach considered caring and the components of it, including compassion, to be moral virtues, an inner motivation to care. This study suggests that without explicit reference to Roach's ideas, and her underlying theoretical base, the CNO requirement has the effect of turning virtues into commodities and a form of external control, described by Ritzer as a McDonaldized dehumanization. This study, which has international relevance beyond England and the UK, suggests that the CNO revise their policy by acknowledging Roach's 6Cs and openly discuss the implications of her work for their policy.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".