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Record W3125579501

A Regulatory-Focused Perspective on Philanthropy: Promotion Focus Motivates Giving to Prevention-Framed Causes

2017· article· en· W3125579501 on OpenAlexaff
Olya Bryksina, Sara Penner

Bibliographic record

VenueSSRN Electronic Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsUniversity of ManitobaUniversity of Winnipeg
Fundersnot available
KeywordsRegulatory focus theoryPersuasionPromotion (chess)Public relationsAppealPerspective (graphical)Framing (construction)DonationBusinessPolitical scienceMarketingPsychologySocial psychologyEngineeringLaw
DOInot available

Abstract

fetched live from OpenAlex

This research employs the framework of Regulatory Focus Theory to examine effectiveness of donation appeals using managerially controllable variables, with results demonstrating objective and implementable outcomes. The results indicate that while individuals’ promotion (vs. prevention) focus motivates philanthropic giving, it is prevention-framed (vs. promotion-framed) causes and appeals that garner greater support from donors. Moreover, we demonstrate that individuals’ promotion focus motivates giving to prevention-framed causes more than to promotion-framed causes. This counter-intuitive finding that persuasion of philanthropy does not function through a traditional regulatory-fit paradigm is an insight with both theoretical and managerial implications. This research leads to the recommendation that to enhance the effectiveness of donation appeals, non-profit managers need to consider message framing, specifically the use of a prevention-framed appeal and a target market of prospective donors with a chronically dominant or situationally activated promotion focus.

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)0.017
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.006
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.029
GPT teacher head0.350
Teacher spread0.320 · 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 designObservational
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

Citations0
Published2017
Admission routes1
Has abstractyes

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