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Record W1759148795 · doi:10.1002/nvsm.1464

Developing personal attachment to a physically active charity event

2013· article· en· W1759148795 on OpenAlexaff
Ryan Snelgrove, Laura Wood, Mark E. Havitz

Bibliographic record

VenueInternational Journal of Nonprofit and Voluntary Sector Marketing · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of WaterlooUniversity of Windsor
Fundersnot available
KeywordsEvent (particle physics)Exploratory researchPsychologySocial psychologyWork (physics)Qualitative researchPublic relationsMarketingApplied psychologyBusinessSociologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Given the commonplace of physically active charity events, it is increasingly important for charitable organizations to understand how participants form personal attachments to their events so that marketers can maximize the amount of funds raised and achieve an attractive return on marketing expenditures. This exploratory study examines the ways in which participants at a walk/run for multiple sclerosis form personal attachments to the event. The limited work that has been conducted in this area has focused on cycling events, which may not include all types of participants (e.g., people with physical restrictions tied to the cause) and their experiences. Data were collected through an online questionnaire that employed open‐ended qualitative questions. The findings suggest three ways in which participants form attachments to the event, including being known as a fundraiser, aligning self and cause, and developing social bonds. Copyright © 2013 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.339
Teacher spread0.309 · 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 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

Citations19
Published2013
Admission routes1
Has abstractyes

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