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Record W3156572983 · doi:10.1177/07439156211014900

Do Consumers Order More Calories in a Meal with a Diet or Regular Soft Drink? An Empirical Investigation Using Large-Scale Field Data

2021· article· en· W3156572983 on OpenAlexaff
Sina Ghotbi, Tirtha Dhar, Charles B. Weinberg

Bibliographic record

VenueJournal of Public Policy & Marketing · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCalorieMealConsumption (sociology)Food scienceExcuseEnvironmental healthMedicineBiology

Abstract

fetched live from OpenAlex

Diet carbonated soft drinks (CSDs) were introduced to help consumers lower caloric intake. However, critics suggest that these drinks can provide an excuse to consume more calories, a so-called “Big Mac and Diet Coke” mentality that is consistent with behavioral theories such as moral licensing (e.g., combining a healthy eating choice with an indulgent, less healthy one). Using individual-level food and drink consumer panel data from a major fast-food restaurant chain, the authors empirically examine meals with a regular CSD versus a diet CSD. Results after controlling for drink size and demographics show that consumers generally do not order higher total calories from a meal with a diet CSD; rather, the authors find significant reductions in calorie count, suggesting that within a single meal, diet CSDs can help consumers unwilling to stop drinking CSDs to reduce calories. So, despite popular beliefs to the contrary, policy makers can consider diet CSD availability as a “calorie-reduction” strategy to lower calorie consumption within a meal.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.313
Teacher spread0.247 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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