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Record W2973910261 · doi:10.1002/arcp.1054

The 3 C's of anthropomorphism: Connection, comprehension, and competition

2019· article· en· W2973910261 on OpenAlexaff
Linyun W. Yang, Pankaj Aggarwal, Ann L. McGill

Bibliographic record

VenueConsumer Psychology Review · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsCompetition (biology)ComprehensionConnection (principal bundle)PsychologyConsumption (sociology)Dimension (graph theory)Social psychologyAdvertisingBusinessAestheticsComputer scienceEngineeringArtMathematics

Abstract

fetched live from OpenAlex

Abstract Anthropomorphism, or imbuing nonhuman entities with human traits, is widely prevalent in the marketplace. The last decade of consumer research demonstrates that when imbued with human characteristics, anthropomorphized brands and products become active participants in the consumption experience and are viewed and treated fundamentally differently than those viewed simply as objects. We identify three dimensions around how consumers relate to anthropomorphized entities: connection, comprehension, and competition. The first two C's highlight how anthropomorphized brands and products benefit consumers by fulfilling belongingness needs (connection) and helping consumers understand unfamiliar situations and products (comprehension). In contrast, the competition dimension highlights how anthropomorphized brands and products are perceived as adversaries or potential threats to consumers’ individual goals. By identifying competition as the third C, we illuminate self‐protection as an additional motivation that shapes consumers’ responses to anthropomorphized entities—a motivation that has not been directly accounted for in previous theorizing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.038
GPT teacher head0.315
Teacher spread0.277 · 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; both teacher heads agree on what is shown here.

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

Citations112
Published2019
Admission routes1
Has abstractyes

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