Demographic Trends in Social Work over a Quarter-Century in an Increasingly Female Profession
Bibliographic record
Abstract
This article depicts the changing demographic portrait of social work education in the United States from 1974 through 2000 and considers the demographic shifts in the profession of social work. During this period, BSW and joint MSW-BSW programs increased from 150 to 404, MSW programs increased from 79 to 139, and social work doctoral programs increased from 29 to 67. BSW graduates increased by 24 percent to almost 12,000, MSW graduates grew by almost 90 percent to over 15,000, and doctoral graduates increased by 44 percent to only 229. From 1974 to 2000, people of color represented increasing proportions of social work graduates to almost 30 percent of BSW graduates, 26 percent of MSW graduates, and 19 percent of social work PhD graduates. By 2000, the proportion of women earning social work degrees had grown to 88 percent at the BSW, 85 percent at the MSW, and 73 percent at the PhD levels, and women accounted for almost two-thirds of social work faculty. The most dynamic trends within the composition of the profession are the substantial increases in the proportion of women faculty, and among MSW graduates, a decrease in the proportion of men from 43 percent in 1960 to 15 percent in 2000. Findings suggest that issues of racial, ethnic, and gender representation in particular merit discussion within 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".