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Record W2594849999 · doi:10.5539/ijms.v9n2p1

Bridging the Gap: Development of the Entrepreneurial Philanthropy Alignment Model

2017· article· en· W2594849999 on OpenAlexvenueno aff
Jos Rath, T.N.M. Schuyt

Bibliographic record

VenueInternational Journal of Marketing Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipBusinessBridging (networking)Harmony (color)MarketingEntrepreneurshipMaturity (psychological)Public relationsPolitical scienceComputer scienceFinance

Abstract

fetched live from OpenAlex

Partnerships are increasingly considered to have the potential to address societal problems that one single actor cannot solve. This paper rationalises the development of partnerships between entrepreneurs and non-profit organisations by the effects of its alignment. In organisations, the process of alignment focuses on the activities that management perform to achieve cohesive goals (e.g., finance, marketing, sales, human resources). Whereas in an entrepreneurial philanthropy partnership, the stage of alignment maturity addresses both how the opted societal change is in harmony with the entrepreneurial approach and how this approach can be in harmony with societal change. This approach is deemed crucial in understanding how the two partners can translate their views on leadership, strategy, and culture into opportunities that enhance their impact. Theoretical researches have provided foundations for identifying dimensions of the conceptual Entrepreneurial Philanthropy Alignment Model (EPAM) that might strengthen the impact of a partnership between an entrepreneur and a non-profit organisation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0060.010
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.088
GPT teacher head0.399
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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