Bibliographic record
Abstract
AIM: The aims of this paper were to explicate clinical scholarship as synonymous with the scholarship of application and to explore the evolution of scholarly practice to clinical scholarship. BACKGROUND: Boyer contributed an expanded view of scholarship that recognized various approaches to knowledge production beyond pure research (discovery) to include the scholarship of integration, application and teaching. There is growing interest in using Boyer's framework to advance knowledge production in nursing but the discussion of clinical scholarship in relation to Boyer's framework is sparse. DESIGN: Discussion paper. DATA SOURCES: Literature from 1983-2015 and Boyer's framework. IMPLICATIONS FOR NURSING: When clinical scholarship is viewed as a synonym for Boyer's scholarship of application, it can be aligned to this well established framework to support knowledge generated in clinical practice. For instance, applying the three criteria for scholarship (documentation, peer review and dissemination) can ensure that the knowledge produced is rigorous, available for critique and used by others to advance nursing practice and patient care. Understanding the differences between scholarly practice and clinical scholarship can promote the development of clinical scholarship. Supporting clinical leaders to identify issues confronting nursing practice can enable scholarly practice to be transformed into clinical scholarship. CONCLUSION: Expanding the understanding of clinical scholarship and linking it to Boyer's scholarship of application can assist nurses to generate knowledge that addresses clinical concerns. Further dialogue about how clinical scholarship can address the theory-practice gap and how publication of clinical scholarship could be expanded given the goals of clinical scholarship is warranted.
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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 | 0.043 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.056 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".