Strategies for Research Development in Hospital Social Work
Bibliographic record
Abstract
Objectives: This article identifies salient components in the advancement of social work research leadership within health care. Method: Using tenets of a modified retrospective case study approach, processes and outcomes of social work research progression at a pediatric hospital are reviewed. Results: Capacity-building processes were implemented. These processes generally corresponded with clinical, research, and administrative priorities and strategically aligned with social work aims of evidence-based practice and research leadership. Elements contributing to improved capacity include clarity of vision, palatable funding models, and the infusion of PhD-trained researchers within the clinical setting. Conclusions: This case study argues for social work to be proactive knowledge leaders. Such an aim, however, inherently requires deliberate shepherding, including strategies to advance the profession.
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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 | 0.441 | 0.297 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.007 |
| Science and technology studies | 0.011 | 0.039 |
| Scholarly communication | 0.030 | 0.025 |
| Open science | 0.010 | 0.038 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".