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Record W3175141932 · doi:10.29173/cjnser.2021v12n1a394

Non-credit Nonprofit Management Education: Beyond Mapping and Towards Critical Qualitative Inquiry

2021· article· en· W3175141932 on OpenAlexaffvenueabout
Michele Fugiel Gartner

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsMount Royal University
Fundersnot available
KeywordsSyllabusPolitical scienceContext (archaeology)HumanitiesLibrary scienceSociologyManagementPedagogyPhilosophyComputer scienceGeographyEconomics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.099
GPT teacher head0.388
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes3
Has abstractyes

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