Nonprofit Education: Course Offerings and Perceptions in Accredited U.S. Business Schools
Bibliographic record
Abstract
Given the continuing need for professional nonprofit managers, a trend toward more businesslike models for administrating nonprofits seems likely. However, the level of business school involvement in the education of future nonprofit managers is largely unknown. Given direction from the Association to Advance Collegiate Schools of Business (AACSB; the premier accreditation body for U.S. business schools) for an education that not only enhances a student's ability to contribute to an organization but to the greater society as well, it seems likely that an increased attention to a curricular focus on business educations that aids the training of future professional nonprofit organization managers might be likely. This study examines the status of nonprofit management, marketing, finance, accounting, social entrepreneurship, social marketing, fundraising courses, programs, and faculty in a sample of U.S. AACSB-accredited business schools. The perceptions of these business schools' leaders with regard to offering or not offering to participate in nonprofit management education are also explored.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".