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Record W2088033275 · doi:10.1509/jm.11.0477

When Does Recognition Increase Charitable Behavior? Toward a Moral Identity-Based Model

2013· article· en· W2088033275 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Marketing · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIdentity (music)InternalizationDonationSocial psychologyMoral behaviorPsychologyAction (physics)Moral disengagementPolitical scienceLaw

Abstract

fetched live from OpenAlex

Each year, people in the United States donate more than $200 billion to charitable causes. Despite the lack of understanding of whether and how recognition increases charitable behavior, charities often offer it to motivate donor action. This research focuses on how the effectiveness of recognition on charitable behavior is dependent on the joint influence of two distinct dimensions of moral identity: internalization and symbolization. Three studies examining both monetary donations and volunteering behavior show that recognition increases charitable behavior among those characterized by high moral identity symbolization and low moral identity internalization. Notably, those who show high levels of moral identity internalization are uninfluenced by recognition, regardless of their symbolization. By understanding correlates of the two dimensions of moral identity among donors, nonprofits can strategically recognize potential donors to maximize donation and volunteering behavior.

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.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.052
GPT teacher head0.304
Teacher spread0.252 · 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