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History of Food Advertising

2024· reference-entry· en· W4400695319 on OpenAlexaff
Sarah Elvins

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAdvertisingArtFood scienceBusinessBiology

Abstract

fetched live from OpenAlex

Abstract Food advertising offers an intriguing window into the cooking and eating habits of a society, is shaped by the culture in which it is produced, and plays a role in creating and reinforcing attitudes about food. Food advertisements reflect and refract larger societal changes in gender roles, racial attitudes, kitchen technology, and more. American food manufacturers in the late 19th century were pioneers in strategies to connect with the public, using advertising to create a new, direct relationship with buyers. This was most prevalent with regard to processed and packaged foods. Ads encouraged consumers to look for specific brand names and to purchase items which might have been made within the home previously. Food manufacturers used a variety of means to encourage and shape consumer practices. Messages emphasizing convenience or modernity were often key to persuading the public to try new products. The strategies developed by American food advertisers were influential around the globe; in some cases, US food products expanded to foreign markets, and in others, local manufacturers employed similar approaches to food advertising. Advertisers in the early 20 century targeted White, middle-class women as the “ideal” consumer. Gender stereotypes about food have often been mobilized by advertisers, creating a vision of family life where a woman’s primary role was to select appropriate foods to serve to her family. In times of change or crisis, advertisers played on anxiety and a longing for stability to encourage people to buy. Company mascots helped to make brands appear friendly and familiar but have also reinforced racist stereotypes about people of color. Critics have blamed food advertisers for changes in eating, which have caused health problems, and for manipulating consumers, particularly children. Although food companies pay millions of dollars for advertising budgets, there is no guarantee that all food ads will be effective. Consumers retain some agency in resisting or reacting to advertisements.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.035
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0040.006
Scholarly communication0.0090.007
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0350.013

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 head0.036
GPT teacher head0.220
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

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