Rationalism in Sally Gadow’s Anti-Rationalist Nursing Ethics
Bibliographic record
Abstract
Carol Gilligan’s seminal critique of Kohlberg’s model of human moral development set on course a major current of postmodern ethical thinking. In a short time, it left in its wake a range of adaptations and elaborations in numerous disciplines, under the title of ‘relational ethics’. One of these adaptations is the “relational narrative” of the philosopher nurse, Sally Gadow, which she proposes as “the postmodern turn in nursing ethics.” Like that of Gilligan, Gadow’s work is a critique of (rational) ethical universalism, which purportedly focused on developing and applying a theory of the ‘good’ to all moral situations. On the contrary, argues Gadow, every moral engagement, such as that between a nursing professional and a patient, comes with inherent unique features that render any attempt at universalization impotent. Every clinical situation is defined by the ability of the professional to engage the client in an intimate, caring relationship that enables healing to take place. Thus, like Gilligan, Gadow aimed to make a clean break from the past, which was dominated by what she referred to as ethical rationalism, by replacing it with the relational approach to ethics, which is based on sympathetic and emotional engagement of patients in the clinic. This paper argues that Gadow’s acclaimed break from the past has not been completely successful. Juxtaposing Gadow’s work with the ideas of the earlier scholars she criticizes, the paper found traces of universalist, rationalist assumptions in her thought going as far back as Descartes and Kant, down to Rawls and Kohlberg. Sources of data for this study were library and archival materials, as well as secondary (Internet) resources, which were subjected to critical and content analysis.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.046 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.001 | 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".