Exploring historical and contemporary fragments of nurses’ invisible practice
Bibliographic record
Abstract
The social context in the hospital setting is fraught with competing and contradictory versions about who nurses are and what they do. Using a sociocultural framework, this thesis provides an analysis of historical and contemporary texts related to hospital-based nursing, and argues that many themes operative in these "official versions" of practice have rendered the breath and complexity of nurses' everyday practices "in/visible." Given that "official versions" of nursing practice are reified in nurses' job descriptions, this research develops a necessarily partial response to the following question: What are nurses' ideas about their in/visible practice within a hospital setting? Nurses’ in/visible practice is, here, defined as the disparity between their "actual" practices, and the job description's "textual representations" of their practice (Smith, 1987 &1990). This investigation took place in an acute care hospital in British Columbia. Seven nurses comprised the primary research group. The research methods used to investigate nurses' in/visible practice included: career autobiographies, direct observation, journals, unstructured one-on-one interviews and concurrent group discussions. Data obtained from these methods underwent qualitative analysis, and both the researcher and the researched (nurses) jointly constructed thematic interpretations of nurses' in/visible practice. This particular analysis of nurses’ in/visible practice suggests that there are "profound" disparities between nurses’ actual practices, and those represented in their job description. Nurses appear to have resisted such textual representations and, in turn, have (re)invented complex theories of "thinking-in-practice," interwoven with an informal "learning with/in practice curriculum."
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.019 | 0.040 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 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".