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Record W3033959345 · doi:10.1002/nvsm.1682

Nonprofit quality: What is it and why should nonprofits care?

2020· article· en· W3033959345 on OpenAlexaff
Parker J. Woodroof, Katharine Howie, Michael C. Peasley

Bibliographic record

VenueJournal of Philanthropy and Marketing · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsNonprofit organizationBusinessTransparency (behavior)Public relationsQuality (philosophy)Corporate governanceContext (archaeology)Nonprofit sectorNon profitMarketingBusiness administrationPolitical science

Abstract

fetched live from OpenAlex

This manuscript examines a quality‐oriented philosophy in a nonprofit context utilizing semi‐structured interviews with nonprofit executive directors. The findings indicate that nonprofit organizations do seek continuous improvement and value a long‐term focus, consistent with for‐profit quality aspirations. However, factors unique to the structure of nonprofit organizations exist and contribute to organizational quality. The interviews converged to highlight five areas that relate to organizational quality in nonprofit organizations: donor relationships, organizational transparency, board member involvement, talent recruitment, and employee commitment. The findings indicate that a quality‐oriented approach to nonprofit governance affects an organization's ability to secure funding and address the mission of the respective organization more efficiently and effectively. Thus, it is suggested that incorporating a quality‐oriented philosophy creates a competitive advantage for nonprofit organizations in an increasingly saturated market.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.097
GPT teacher head0.383
Teacher spread0.286 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations9
Published2020
Admission routes1
Has abstractyes

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