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Record W4386814840 · doi:10.22434/ifamr2022-0150

Cheese without cows: Consumer demand for animal-free dairy cheese made from cellular agriculture in the United Kingdom

2023· article· en· W4386814840 on OpenAlexaff
Peter Slade, Oscar Zollman Thomas

Bibliographic record

VenueThe International Food and Agribusiness Management Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBusinessAgricultural scienceAgricultural economicsDairy industryLivestockDairy cattleAgricultureEconomicsFood scienceAnimal scienceBiology

Abstract

fetched live from OpenAlex

Abstract We examine consumer demand for animal-free dairy cheese produced using cellular agriculture. Our data is generated through a hypothetical choice experiment completed by 1249 UK residents. Using a mixed logit model, we predict that animal-free dairy cheese would have a conditional market share of 22% when priced at a 25% markup relative to premium conventional cheese. However, the market share is quite sensitive to price: only 2% of consumers would purchase animal-free dairy cheese if it were twice the price of premium conventional cheese. Three-quarters of consumers who purchase animal-free dairy cheese would have purchased conventional dairy cheese if animal-free dairy cheese were unavailable. We use our experimental results to examine the impact of higher conventional dairy cheese prices, such as those that might result from a tax on livestock products. We find that the introduction of animal-free dairy cheese reduces consumer losses from higher conventional dairy prices by about 20%.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.101
GPT teacher head0.249
Teacher spread0.148 · 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 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

Citations9
Published2023
Admission routes1
Has abstractyes

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