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Record W2048724698 · doi:10.1108/17473610610718008

Blame our evolved gustatory preferences

2006· article· en· W2048724698 on OpenAlexaff
Gad Saad

Bibliographic record

VenueYoung Consumers Insight and Ideas for Responsible Marketers · 2006
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsConcordia University
Fundersnot available
KeywordsBlameOriginalityValue (mathematics)Childhood obesityConsumption (sociology)PsychologySocializationEvolutionary psychologySocial psychologyCognitive psychologyObesitySociologySocial scienceOverweightBiologyCreativity

Abstract

fetched live from OpenAlex

Purpose To argue that childhood obesity is minimally influenced by media sources. Rather, our evolved gustatory preferences for fatty and sweet caloric foods, which were adaptive in our evolutionary history, yield maladaptive outcomes in today’s plentiful environments. Design/methodology/approach The approach is discursive relying on several literature streams to make the key points of the current paper. Findings Obesity, whether in children, adolescents, or adults, is minimally linked to media images. The “media‐obesity” postulated relationship stems from the blank slate viewpoint of the human mind, which places undue importance on environmental cues and related socialization forces. Research limitations/implications Highlights the fact that social scientists have expended too much intellectual capital in investigating largely illusory links between food advertising and childhood obesity, when in reality this relationship is tenuous at best. Practical implications Policy makers should spend less time worrying about the regulation of media images as these have little effect on behaviors with deleterious consequences (including childhood obesity). Originality/value One of the few papers (if not the only one) in the marketing literature to apply evolutionary‐based theorizing in understanding the forces that shape individuals’ food consumption habits.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
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)0.0000.000

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 head0.019
GPT teacher head0.294
Teacher spread0.275 · 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

Citations7
Published2006
Admission routes1
Has abstractyes

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