Interpretive description: a viable methodological approach for nursing research
Bibliographic record
Abstract
Abstract Objective: To present a theoretical reflection about the origin and the assumptions of the "Interpretive Description" method, and to discuss its applicability in Nursing and Health research. Method: Theoretical-reflective study, based on articles and books published by proponent of this approach, as well as scientific articles in which the authors reported having used this method in their studies. Results: It was evidenced that the "Interpretive Description" arose from the need to generate a better understanding of clinical practices in Nursing. This approach has its roots in the methodological traditions of the Social Sciences, although it differs from them in terms of its excessive rigidity and essentially theoretical objectives. The proposed method has been applied in several studies either in Nursing as other areas of Health. Conclusion: The "Interpretive Description" is considered a feasible approach for the production of knowledge in Applied Sciences such as Nursing.
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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 | 0.251 | 0.207 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.012 | 0.007 |
| Science and technology studies | 0.007 | 0.049 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".