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Record W2758641126 · doi:10.1093/jcr/ucx101

When Public Recognition for Charitable Giving Backfires: The Role of Independent Self-Construal

2017· article· en· W2758641126 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 Consumer Research · 2017
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of British ColumbiaWestern University
Fundersnot available
KeywordsSelf construalDonationInterdependenceConstrual level theorySocial psychologyPsychologyPublic goodPolitical scienceEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

Abstract This research examines the effectiveness of public recognition in encouraging charitable giving, demonstrating that public recognition can sometimes decrease donations. While previous work has largely shown that making donations visible to others can motivate donors, the present research shows that the effectiveness of public recognition depends on whether potential donors are under an independent (i.e., separate from others) or interdependent (i.e., connected with others) self-construal. Across seven experimental studies, an independent self-construal decreases donation intentions and amounts when the donor will receive public recognition compared to when the donation will remain private. This effect is driven by the activation of an agentic motive, wherein independents are motivated to make decisions that are guided by their own goals and self-interests, rather than being influenced by the opinions and expectations of others. This research contributes to the understanding of the nuanced roles of both public recognition and self-construal in predicting donation 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)0.004
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.335
GPT teacher head0.467
Teacher spread0.132 · 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