Operationalizing Evidence-Based Practice
Bibliographic record
Abstract
Although evidence-based practice (EBP) has received increasing attention in social work in the past few years, there has been limited success in moving from academic discussion to engaging social workers in the process of implementing EBP in practice. This article describes the challenges, successes, and future aims in the process of developing a university-based institute for evidence-based social work. Aspects of the development include attempting to address concerns and critiques through developing an inclusive model of EBP; engaging community agency partners as active participants in the process; developing collaborative research projects with community partners to further the research evidence available for practice; conducting systematic reviews; finding means of disseminating review and research findings broadly in order to effect social policy revisions and lead to the development of effective programs and practices; and training agency personnel and social work students in the process of EBP and conducting practice evaluation research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.390 | 0.553 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.032 | 0.014 |
| Science and technology studies | 0.006 | 0.038 |
| Scholarly communication | 0.030 | 0.021 |
| Open science | 0.009 | 0.026 |
| Research integrity | 0.012 | 0.010 |
| 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".