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Record W2394577982 · doi:10.4038/jas.v3i1.8143

Use of Caswell’s classification on food quality attributes to assess consumer perceptions towards fresh milk in tetra-packed containers

2007· article· en· W2394577982 on OpenAlexaff
Sumudu Kariyawasam, U. K. Jayasinghe-Mudalige, Jeevika Weerahewa

Bibliographic record

VenueJournal of Agricultural Sciences – Sri Lanka · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsQuality (philosophy)Marital statusLogistic regressionStatisticMarketingBusinessIndex (typography)Agricultural scienceFood qualityGovernment (linguistics)PerceptionValue (mathematics)Food scienceStatisticsMathematicsEnvironmental healthPsychologyMedicinePopulationComputer scienceEnvironmental science

Abstract

fetched live from OpenAlex

This study assesses, using the Caswell’s classification on food quality attributes (1998), what quality attributes that consumers consider most important in their decision to purchase fresh milk stored in tetra-pack containers, and the impact of a number of socio-economic characteristics of consumers on this behavior. A consumer survey was carried out (n=664) in the Gampaha district from April to May in 2005, and data pertaining to 100 who consume it with the highest frequency (i.e. 3.43 packs/week) were considered for the empirical analysis. The results based on two indices, namely the “Mean Score of Quality Attribute” (MSQA) and the “Food Quality Responsive Index” (FQRI) suggest that attributes such as purity, appearance, size, convenience, and informational labeling from “value” and “package” subsets were the most important. It also shows that consumers did not judge that tetra-packs enhance attributed included in the “food safety” and “nutrition” subsets to a larger extent. The statistic outcome based on Ordered Logistic regression techniques, where the values of FQRI were used to develop four dependent variables, shows that factors such as age, marital status, sex, and level of education and income of a consumer have a significant impact on this behavior. The results suggest that the market can work effectively on promoting the sales of fresh milk by enhancing its quality in terms of value and packaging attributes, while the government should take into account of regulating the attributes of food safety and nutrition through appropriate food standards.

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)0.001
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 score0.081
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.187
GPT teacher head0.346
Teacher spread0.159 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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