Discursive practice – lean thinking, nurses’ responsibilities and the cost to care
Bibliographic record
Abstract
PURPOSE: The purpose of this paper is to explore the literature regarding work intensification that is being experienced by nurses, to examine the effects this is having on their capacity to complete care. The authors contend that nurses' inability to provide all the care patients require, has negative implications on their professional responsibility. DESIGN/METHODOLOGY/APPROACH: The authors used institutional ethnography to review the discourse in the literature. This approach supports inquiry through the review of text in order to uncover activities that remain institutionally accepted but unquestioned and hidden. FINDINGS: What the authors found was that the quality and risk management forms an important part of lean thinking, with the organisational culture influencing outcomes; however, the professional cost to nurses has not been fully explored. RESEARCH LIMITATIONS/IMPLICATIONS: The text uncovered inconsistency between what organisations accepted as successful cost savings, and what nurses were experiencing in their attempts to achieve the care in the face of reduced time and human resources. Nurses' attempts at completing care were done at the risk of their own professional accountability. PRACTICAL IMPLICATIONS: Nurses are working in lean and stressful environments and are struggling to complete care within reduced resource allocations. This leads to care rationing, which negatively impacts on nurses' professional practice, and quality of care provision. ORIGINALITY/VALUE: This approach is a departure from the standard qualitative review because the focus is on the textual relationships between what is being advocated by organisations directing cost reduction and what is actioned by the nurses working at the coalface. The discordant standpoints between these two juxtapositions are identified.
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.
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 | 0.026 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.054 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".