Enhancing Social Work Research Education Through Research Field Placements
Bibliographic record
Abstract
The increase focus on the role of research in the social service sector, pressure for practitioners to engage in research and the demand for integration of research and practice challenges faculties about ways in which to engage social work students in research. This paper evaluates a research based practicum program within a social work faculty at one Canadian university aimed at meeting this need. The objectives of the practicum include providing opportunities to integrate research theory/methods with practice; develop a broad range of research knowledge and skills; reduce negative stereotypes; instill passion and excitement for research; and connect students with agencies to engage in community based research. The mixed methods evaluation of the practicum included semi-structured qualitative interviews with former and current directors (n=2); an online survey with past practicum students (n=15); and a pre- and post-test attitude/skills assessment, a self reflection journal exercise, and a focus group with students currently in practicum (n=7). Findings suggest benefits of the research practicum across stakeholders as well as several challenges and opportunities for program enhancement. Research practicum is an innovative way of engaging students in applied research which can augments research capacity, mitigate negative stereotypes about research, and better prepare future social work practitioners.
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 | 0.051 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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".