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Record W2285915258 · doi:10.5539/jfr.v5n1p107

Employee and Customer Reactions to a Healthy In-Store Marketing Intervention in Supermarkets

2016· article· en· W2285915258 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Food Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingBusinessDemographicsPurchasingDirect marketingStaffingProduct (mathematics)Variance (accounting)Test (biology)AdvertisingEconomics

Abstract

fetched live from OpenAlex

Supermarkets are a primary source of food for American households, and increased presence in low-income, high-minority neighborhoods present opportunities to increase access to healthy foods. It is important to assess store manager and customer reactions to in-store marketing interventions. The objective was to evaluate manager and customer reactions to stealth, low-cost, sustainable in-store marketing strategies to promote healthier purchases in five product categories and gain insight into shopping habits and willingness to change behaviors. Surveys were collected as part of the evaluation of a cluster-randomized controlled trial conducted from 2011-2012 in eight urban supermarkets in low-income, high-minority neighborhoods. Store manager (n=16) and customer intercept surveys (n=100) were administered at intervention stores in May-July 2012 and August 2012, respectively. Demographics, shopping habits, and impact were calculated using frequency distributions, cross-tabulation, and analyses of variance. Correlations were calculated using Pearson’s R or one-sided Fisher’s Exact Test. Most managers reported the project had a positive impact on stocking, ordering, staffing, and interaction with other employees. Most customers did not notice new marketing strategies, although they were intentionally stealth. A large number of customers reported making impulse purchases regularly. Opportunities to positively affect purchasing may exist.

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.

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)0.006
metaresearch head score (Gemma)0.002
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 score0.141
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.102
GPT teacher head0.379
Teacher spread0.278 · 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