The value of measurement for development of nursing knowledge: Underlying philosophy, contributions and critiques
Bibliographic record
Abstract
AIM: A philosophical discussion of constructive realism and measurement in the development of nursing knowledge is presented. BACKGROUND: Through Carper's four patterns of knowing, nurses come to know a person holistically. However, measurement as a source for nursing knowledge has been criticized for underlying positivism and reductionist approach to exploring reality. Which seems mal-alignment with person-centred care. DESIGN: Discussion paper. DISCUSSION: Constructive realism bridges positivism and constructivism, facilitating the measurement of physical and psychological phenomena. Reduction of complex phenomena and theoretical constructs into measurable properties is essential to building nursing's empiric knowledge and facilitates (rather than inhibits) person-knowing. IMPLICATIONS FOR NURSING: Nurses should consider constructive realism as a philosophy to underpin their practice. This philosophy supports measurement as a primary method of inquiry in nursing research and clinical practice. Nurses can carefully select, and purposefully integrate, measurement tools with other methods of inquiry (such as qualitative research methods) to demonstrate the usefulness of nursing interventions and highlight nursing as a science.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".