Non-credit Nonprofit Management Education: Beyond Mapping and Towards Critical Qualitative Inquiry
Bibliographic record
Abstract
Nonprofit management education (NME) has received attention from scholars and practitioners over the past thirty years. Much of the research on NME focuses on credit-based university courses, primarily reflecting a U.S. context. Left out of analyses are non-credit NME offerings. This article relocates to an English-speaking Canadian landscape where a substantial number of non-credit NME courses are found. Mapping methodologies, favoured to showcase the breadth of NME, cannot offer deeper insight into questions and critiques of non-credit NME curriculum and instruction. This article shows how syllabi review and critical qualitative inquiry can deepen knowledge of non-credit offerings. A new research agenda for non-credit NME is required to support nonprofit managers to achieve their social goals. RÉSUMÉDepuis une trentaine d’années, la formation en gestion des organismes sans but lucratif (OSBL) a retenu l’attention d’universitaires et de praticiens. Cependant, une grande partie de leurs recherches sur la gestion des OSBL se concentre sur des cours universitaires offrant des crédits, et reflète un contexte principalement américain. Les cours sans crédit sur la gestion des OSBL sont omis des analyses. Cet article se focalise sur un paysage canadien anglophone où l’on retrouve un nombre important de cours sans crédit sur la gestion des OSBL. Certaines méthodologies de schématisation, privilégiées pour mettre en valeur la portée de tels cours, sont inefficaces pour offrir un aperçu plus approfondi des questions et critiques concernant le curriculum et l’enseignement de cours sans crédit sur la gestion des OSBL. Cet article montre comment la revue de plans de cours et l’enquête qualitative critique peuvent en revanche servir à approfondir la connaissance de ces cours sans crédit. Ainsi, un nouveau programme de recherche pour les cours sans crédit sur la gestion des OSBL s’avère nécessaire pour aider les gestionnaires d’OSBL à atteindre leurs objectifs sociaux.
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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 | 0.060 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".