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Record W3094856598 · doi:10.1177/1012690220968107

When the gift is halfhearted: A socio-cultural study of ambivalence in a charity sport event

2020· article· en· W3094856598 on OpenAlexaff
Ayelet Oreg, Itay Greenspan, Ida E. Berger

Bibliographic record

VenueInternational Review for the Sociology of Sport · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAmbivalenceFeelingSocial psychologyExtant taxonSet (abstract data type)Exploratory researchPsychologySociologyPublic relationsPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Taking a culturally sensitive approach, we set out to explore the social response to, and the cultural adoption of, charity sport events in Israel, where this phenomenon is relatively new and understudied. We show that charity sport events participation is accepted with mixed feelings: participants are motivated by their novice athletic aspirations and love for bike riding, and by their emotional connection to the cause, but at the same time are reluctant to fundraise and donate due to socio-cultural barriers. Using a qualitative, exploratory, single case study design, and relying on the literature of charity sports events, we show that in contrast to the extant distinction between philanthropic givers’ motivations and non-givers’ barriers, participants in charity sport events experience simultaneous motivations for and barriers to their own philanthropic giving. Although they strongly identify with their role as bike riders, and are motivated to take part in a challenging ride, they struggle with the roles of fundraiser and philanthropist that are inherent components of charity sports events. The combination of these experiences yields the experience of ambivalence towards philanthropic giving, which we accordingly term as ambivalent philanthropy .

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)0.000
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 score0.080
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.079
GPT teacher head0.399
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 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

Citations5
Published2020
Admission routes1
Has abstractyes

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