Nursing Against the Odds: How Health Care Cost Cutting, Media Stereotypes, and Medical Hubris Undermine Nurses and Patient care
Bibliographic record
Abstract
Nursing Against the Odds: How Health Care Cost Cutting, Media Stereotypes, and Medical Hubris Undermine Nurses and Patient care Suzanne, Gordon , 2005 ; ILR Press, an imprint of Cornell University Press, Ithaca, New York and London : 489 pages. ISBN: 0-8014-3976-0 . Nursing against the Odds should be on every nurse's booklist and is essential reading for anyone remotely interested in the politics of nursing. Suzanne Gordon is an award-winning journalist who has written two previous books on aspects of nursing as well as numerous articles in the American and Canadian press. She is Assistant Adjunct Professor at the University of California at San Francisco School of Nursing and also edits with Siobhan Nelson (Editor of Nursing Inquiry) a series of books on The Culture and Politics of Health Care Work. In addition to this impeccable pedigree, Suzanne Gordon writes in an immensely knowledgeable and readable style. She is up-to-date with all the current issues that preoccupy nurses and she writes about them with deep understanding and lucidity. Perhaps her greatest credit is that she covers all the arguments, both for and against a particular approach to every issue. In doing so she dispels any notion that this is yet another book about ‘whingeing nurses’. In the first of three sections she covers Nurses and Doctors at Work and explores all the well-worn themes in a fresh and lively style. Gordon's approach to the second section, The Media and Nursing, is fairly novel. She starts with how children are imbued with certain stereotypes of nurses through books at the beginning of their lives. She goes onto adult forms of indoctrination (for example, Nurse Ratched in One Flew over the Cuckoo's Nest and Sarah Gamp in Martin Chuzzlewit) and then examines nurses in TV and film. In the third and most important section, Hospitals and Nursing, Gordon is at her best when writing about the impact of cost cutting and hospital re-structuring on nursing. A typical example comes from her own experience. When asked by a critical care journal to write about patient-centred care, she found that the nurses interviewed were less than enthusiastic, even hostile, to the concept. Gordon soon discovered why: I didn’t have to dig far before I discovered that patient-centred or patient-focused care was a central building stone in the restructuring and reengineering of health care. It was one of those Orwellian formulations used to describe its opposite. Under the guise of patient-centred, patient-focused care, nurses quickly told me, they were losing their ability to centre on the patient and were increasingly asked to focus on profit (p. 229). In her Conclusion, Changing the Odds, Gordon considers the various options available to address the current crisis in nursing, whilst recognizing that many of nurses’ would-be solutions are ‘off limits’. In these final pages Gordon underestimates the immense political forces in the USA that oppose any change to its inequitable and hugely wasteful health care system (think of Hillary Clinton failing dismally to achieve health care reform during her husband's presidency). She also tends to view the rest of the world through somewhat rose-tinted spectacles. But these are small complaints about an immensely courageous book.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".