Public Health and Social Work: Training Dual Professionals for the Contemporary Workplace
Bibliographic record
Abstract
OBJECTIVES: The emergence of new, complex social health concerns demands that the public health field strengthen its capacity to respond. Academic institutions are vital to improving the public health infrastructure. Collaborative and transdisciplinary practice competencies are increasingly viewed as key components of public health training. The social work profession, with its longstanding involvement in public health and emphasis on ecological approaches, has been a partner in many transdisciplinary community-based efforts. The more than 20 dual-degree programs in public health and social work currently offered reflect this collaborative history. This study represents an exploratory effort to evaluate the impact of these programs on the fields of public health and social work. METHODS: This study explored motivations, perspectives, and experiences of 41 graduates from four master of social work/master of public health (MSW/ MPH) programs. Four focus groups were conducted using traditional qualitative methods during 2004. RESULTS: Findings suggest that MSW/MPH alumni self-selected into dual programs because of their interest in the missions, ethics, and practices of both professions. Participants highlighted the challenges and opportunities of dual professionalism, including the struggle to better define public health social work in the workplace. CONCLUSIONS: Implications for academic public health focus on how schools can improve MSW/MPH programs to promote transdisciplinary collaboration. Increased recognition, better coordination, and greater emphasis on marketing to prospective employers were suggested. A national evaluation of MSW/MPH graduates could strengthen the roles and contributions of public health social work to the public health infrastructure. A conceptual framework, potentially based on developmental theory, could guide this evaluation of the MSW/MPH training experience.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".