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Record W1969421897 · doi:10.1300/j054v19n02_03

The Grape Escape–A FUNdraising Bike Tour for the Multiple Sclerosis Society

2008· article· en· W1969421897 on OpenAlexaff
Joan Higgins, Ashley Hodgins

Bibliographic record

VenueJournal of Nonprofit & Public Sector Marketing · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEvent (particle physics)MarketingBusinessPerceptionSocial marketingPublic relationsMarketing communicationCompetition (biology)AdvertisingPsychologyPolitical science

Abstract

fetched live from OpenAlex

As the fundraising climate for nonprofit organizations becomes increasingly competitive for the public's attention and charitable giving, social marketing research can help to gather information for mutual benefit. This paper describes a study that evaluated a weekend cycling fundraising event for the Multiple Sclerosis Society to better understand participants' experiences and improve the event. Data were collected via questionnaires (n = 78) revealing perceptions of the benefits and costs of participation, as well as cyclists' ratings of self and external efficacy. Telephone interviews (n = 25) captured participants' reactions to the event's marketing materials and communication strategies. Implications for improving the event to maximize benefits and reduce costs, enhance its marketing, recruit future and retain existing participants and positioning the event are offered.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.128
GPT teacher head0.291
Teacher spread0.164 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations18
Published2008
Admission routes1
Has abstractyes

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