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Record W2160462213 · doi:10.5539/jfr.v4n3p89

Why Are Alternative Diets Such as “Low Carb High Fat” and “Super Healthy Family” So Appealing to Norwegian Food Consumers?

2015· article· en· W2160462213 on OpenAlexvenueno aff
Annechen Bahr Bugge

Bibliographic record

VenueJournal of Food Research · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsNorwegianConsumption (sociology)Product (mathematics)AdvertisingFood scienceDreamMarketingBusinessPsychologySociologySocial scienceBiologyMathematics

Abstract

fetched live from OpenAlex

<p>Aspiring for health and fitness has become increasingly important for Norwegians. This is expressed in many ways. For instance there has been a significant increase in the proportion who states that they are very interested in having a healthy diet. Furthermore, three out of ten stated that they had tried diets to achieve weight reduction over the past twelve months. One consequence of this trend is a consumption field that requires a multitude of products and services. This includes everything from food and dietary products that help you realize the dream of a sound, slim, strong, smart and sexy body, to books, blogs and TV shows that guide the individual towards making the right food choices. Through media, books and product launches, consumers are continuously exposed to different theories and beliefs about what and how to eat. A typical characteristic of the diets that have gained wide acceptance over the past few years is that they are in conflict with the national guidelines for a healthy diet. Another tendency is that traditional products in the Norwegian diet such as bread, potatoes and dairy products, in particular, have been up for debate. The purpose of this article is to explore why these alternative and rebellious diets have become so appealing to today’s food consumer. Data are derived from both quantitative and qualitative materials.</p>

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.308

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 science0.0000.000
Research integrity0.0000.001
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 head0.127
GPT teacher head0.345
Teacher spread0.217 · 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 designNot applicable
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

Citations16
Published2015
Admission routes1
Has abstractyes

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