Lamentation and loss: expressions of caring by contemporary surgical nurses
Bibliographic record
Abstract
AIM: This paper is a report of a phenomenological study of caring from the perspective of nurses working on surgical wards. BACKGROUND: While care and caring are complex foundational nursing concepts which have received considerable and ongoing attention from theorists, researchers and clinicians, there has been little research into caring on surgical units. METHOD: A convenience sample of ten nurses working on surgical units in a public teaching hospital in Canada was interviewed using van Manen's phenomenological approach. Data were collected during 2001 using semi-structured interviews. FINDINGS: The major theme of lamentation and loss was identified from the data. Participants revealed a dichotomous tension between what caring should be and what actually occurs. This tension was pervasive and generated lament - an expression of grief and mourning for the loss of caring. The essential structures supporting this theme included lack of time, lack of caring support, tasking, increased acuity, lack of continuity of care, emotional divestment and not caring for each other. Loss and sadness were articulated and participants lamented and grieved about the loss of care in contemporary practice. CONCLUSION: The forces and influences described by participants undermined caring in the new practice milieu. If this is a glimpse of the future, then the values of the nursing profession may be under siege. Caring as the central core, the essence or unifying concept of nursing may be subject to marginalization in contemporary 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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".