Technologically-Mediated Nursing Care: the Impact on Moral Agency
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Technology is pervasive and overwhelming in the intensive care setting. It has the power to inform and direct the nursing care of critically ill patients. Technology changes the moral and social dynamics within nurse-patient encounters. Nurses use technology as the main reference point to interpret and evaluate clinical patient outcomes. This shapes nurses' understanding and the kind of care provided. Technology inserts itself between patients and nurses, thus distancing nurses from patients. This situates nurses into positions of power, granting them epistemic authority, which constrains them as moral agents. Technology serves to categorize and marginalize patients' illness experience. In this article, moral agency is examined within the technologically-mediated context of the intensive care unit. Uncritical use of technology has a negative impact on patient care and nurses' view of patients, thus limiting moral agency. Through examination of technology as it frames cardiac patients, it is demonstrated how technology changes the way nurses understand and conceptualize moral agency. This article offers a new perspective on the ethical discussion of technology and its impact on nurses' moral agency. Employing reflective analysis using the technique of embodied reflection may help to ensure that patients remain at the centre of nurses' moral practice. Embodied reflection invites nurses critically to examine how technology has reshaped conceptualization, understanding, and the underlying motivation governing nurses' moral agency.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.032 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it