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Record W4403000195 · doi:10.1080/10495142.2024.2408569

Effects of Moral Claims on Charitable Support for the Stigmatized

2024· article· en· W4403000195 on OpenAlexafffund
Robert J. Fisher, Katherine C. Lafreniere, Ernan Haruvy

Bibliographic record

VenueJournal of Nonprofit & Public Sector Marketing · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsMcGill UniversityUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSociologySocial psychologyBusinessPublic relationsEnvironmental ethicsPsychologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

In this research, we examine the extent to which charitable support for the stigmatized can be enhanced by a moral claim, which occurs when a stigmatized person is attributed an unselfish (versus self-interested) motive for a socially desirable behavior. We find that prospective donors infer a more positive morality when a moral claim is made about a stigmatized person in need, which leads to a greater willingness to provide them with charitable support. The effect does not occur when the same moral claim is made for a person in equivalent need who is accepted or honored in society. We find that moral claims are effective when based on unsubstantiated statements about a mentally ill person’s morality (Study 1), when a drug thief volunteers to help flood victims, rather than helps them as part of her employment (Study 2), and when a homeless criminal returns a lost wallet to do the right thing, rather than to receive a reward (Study 3). The research contributes to our understanding of the role of moral judgments that lead to social rejection and provides insights into how the negative stereotypes that affect the stigmatized can be changed.

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)0.012
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.049
GPT teacher head0.348
Teacher spread0.299 · 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 designNot applicable
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

Citations2
Published2024
Admission routes2
Has abstractyes

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