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Record W2757065318 · doi:10.1177/2051570717733411

Shock charity campaigns: Building our understanding on their effectiveness: Comments on “Emotions and Prosocial Behaviors: A Study of the Effectiveness of Shocking Charity Campaigns” by Jeanne Albouy

2017· article· en· W2757065318 on OpenAlexaff
Darren W. Dahl

Bibliographic record

VenueRecherche et Applications en Marketing (English Edition) · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProsocial behaviorContext (archaeology)Shock (circulatory)EmpathyAdvertisingPublic relationsSocial psychologyWork (physics)PsychologyPolitical scienceBusinessMedicineEngineering

Abstract

fetched live from OpenAlex

The recent article entitled “Emotions and Prosocial Behaviors: A Study of the Effectiveness of Shocking Charity Campaigns” authored by Jeanne Albouy published in Recherche et Applications en Marketing provides important evidence on the effectiveness of shocking advertisements in the context of charity appeals. Specifically, this research highlights how the negative emotions and empathy that are produced by shock campaigns lead to positive attitudes toward the ad, the cause, and the intentions to help the charity. This work is important because it helps to resolve a conflict in the literature – namely, divergent findings that have shown both positive and negative outcomes for ads in charity campaigns that are emotional and raw in nature. Furthermore, like any good research, this work also seeds new opportunities for future investigation into the role of shock advertising in the context of charity communication campaigns. This commentary will look to highlight where additional research opportunities exist. Specifically, the discussion will center on three directions of potential interest: (1) a broader investigation into the notion of shock advertising in the context of charity campaigns, (2) understanding potential differences in how an audience is exposed to shock advertising and the implications therein, and (3) contemplating other outcome measures that could provide meaningful insight into how shock advertising has an impact in the marketplace.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.112
GPT teacher head0.355
Teacher spread0.243 · 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.

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
Published2017
Admission routes1
Has abstractyes

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